Upload best model checkpoint
Browse files- config.json +38 -0
- generation_config.json +6 -0
- merges.txt +0 -0
- metrics.json +31 -0
- model.safetensors +3 -0
- special_tokens_map.json +6 -0
- tokenizer.json +0 -0
- tokenizer_config.json +21 -0
- train_configs.json +112 -0
- vocab.json +0 -0
config.json
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{
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"activation_function": "gelu_new",
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"architectures": [
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"GPT2LMHeadModel"
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],
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"attn_pdrop": 0.1,
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"bos_token_id": 50256,
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"dtype": "float32",
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"embd_pdrop": 0.1,
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"eos_token_id": 50256,
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"initializer_range": 0.02,
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"layer_norm_epsilon": 1e-05,
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"model_type": "gpt2",
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"n_ctx": 1024,
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"n_embd": 768,
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"n_head": 12,
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"n_inner": null,
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"n_layer": 12,
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"n_positions": 1024,
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"reorder_and_upcast_attn": false,
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"resid_pdrop": 0.1,
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"scale_attn_by_inverse_layer_idx": false,
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"scale_attn_weights": true,
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"summary_activation": null,
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"summary_first_dropout": 0.1,
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"summary_proj_to_labels": true,
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"summary_type": "cls_index",
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"summary_use_proj": true,
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"task_specific_params": {
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"text-generation": {
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"do_sample": true,
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"max_length": 50
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}
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},
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"transformers_version": "4.57.3",
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"use_cache": true,
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"vocab_size": 50257
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}
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generation_config.json
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{
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"_from_model_config": true,
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"bos_token_id": 50256,
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"eos_token_id": 50256,
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"transformers_version": "4.57.3"
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}
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merges.txt
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metrics.json
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{
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"rl_info/A2G": -0.6658737659454346,
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"rl_info/entropy": 0.7045262455940247,
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"rl_info/total_token": 650.0,
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"rl_info/advantage_b4_norm": -2206.338134765625,
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"rl_info/advantage_after_gnorm": -1.0411098003387451,
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"rl_info/kl_w_ref": -0.0003157879982609302,
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"rl_info/clip_ratio": 0.936923086643219,
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"train/rl_loss": 66.5872802734375,
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"train/total_loss": 8.323410034179688,
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"xsum/rouge1": 0.17478446053644453,
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"xsum/rouge2": 0.0270244843023609,
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"xsum/rougeL": 0.13926067850589546,
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"xsum/rougeLsum": 0.14284803751147157,
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"xsum/bertscore_precision": 0.7250652085152888,
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"xsum/bertscore_recall": 0.7281463338055265,
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"xsum/bertscore_f1": 0.7262238959629153,
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"eval_agg/avg_all_rougef": 0.12097941521404312,
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"eval_agg/avg_all_bertf": 0.7262238959629153,
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"eval_agg/avg_all": 0.4236016555884792,
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"num_rl_rollout": 250,
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"lm_epoch": 0,
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"rl_epoch": 0,
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"step": 2000,
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"total_data_token": 3685864,
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"total_rl_token": 8807121,
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"total_lm_token": 0,
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"total_token": 8807121,
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"completed_steps": 2000,
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"tune_objective": 0.41038940313189515
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}
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model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:5dc913c5fe263bf822ac5cea8b4d84459769d9fc569cda85f78bdccc846ddd7e
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size 497774208
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special_tokens_map.json
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{
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"bos_token": "<|endoftext|>",
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"eos_token": "<|endoftext|>",
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"pad_token": "<|endoftext|>",
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"unk_token": "<|endoftext|>"
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}
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tokenizer.json
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tokenizer_config.json
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{
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"add_prefix_space": false,
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"added_tokens_decoder": {
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"50256": {
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"content": "<|endoftext|>",
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"lstrip": false,
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"normalized": true,
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"rstrip": false,
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"single_word": false,
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"special": true
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}
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},
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"bos_token": "<|endoftext|>",
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"clean_up_tokenization_spaces": false,
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"eos_token": "<|endoftext|>",
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"extra_special_tokens": {},
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"model_max_length": 1024,
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"pad_token": "<|endoftext|>",
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"tokenizer_class": "GPT2Tokenizer",
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"unk_token": "<|endoftext|>"
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}
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train_configs.json
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{
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"dataset_name": "nbtpj/summ_ds_train",
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"dataset_config_name": null,
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"train_split_name": "sim_with_one_golden__xsum_train",
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"text_template": "{text}\nTL;DR: {summary}",
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"label_col": "summary",
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"freeze_role2": true,
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"only_train_role1": true,
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"model_name_or_path": "gpt2",
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"ref_role1_name_or_path": "nbtpj/summ_gpt2_tldr_xsum",
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"ref_role2_name_or_path": "gpt2",
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"pretrained_role2_name_or_path": "gpt2",
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"config_name": null,
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"vectorizer_path": "/common/home/users/m/mq.nguyen.2023/testcode/SAC_LM/module9_clmv3/vectorizer/wikitext103_tfidf_full.joblib",
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| 15 |
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"tokenizer_name": null,
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"use_slow_tokenizer": false,
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"per_device_train_batch_size": 16,
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"per_device_query_rollout_batch_size": 32,
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"per_device_eval_batch_size": 16,
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"vllm_vram_ratio": 0.3,
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"learning_rate": 3e-07,
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"grad_norm": 0.5,
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"weight_decay": 1e-05,
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"max_train_steps": 100000,
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"max_train_rollouts": 100000,
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| 26 |
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"gradient_accumulation_steps": 1,
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"lr_scheduler_type": "constant",
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"num_warmup_steps": 200,
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"seed": 0,
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"model_type": null,
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"block_size": 1024,
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"mini_epoch": 2,
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"rollout_game": "baseline3v2",
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"rl_algo": "on_policy",
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"constraint_type": "kl",
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"clamp_update": false,
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"clamp_ref": true,
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"no_is_correction": false,
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"rl_w": 1.0,
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| 40 |
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"lm_w": 0.0,
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| 41 |
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"n_generate": 4,
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| 42 |
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"n_augment": 0,
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"gradient_checkpoint": false,
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| 44 |
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"group_relative_norm": true,
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"sample_config": {
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| 46 |
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"do_sample": true,
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| 47 |
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"min_new_tokens": 5,
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| 48 |
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"temperature": 1.0
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| 49 |
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},
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| 50 |
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"inference_config": {
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| 51 |
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"do_sample": true,
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| 52 |
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"temperature": 0.0,
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| 53 |
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"min_new_tokens": 15,
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| 54 |
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"max_new_tokens": 40
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},
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"rollout_config": {
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| 57 |
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"accuracy_w": 1000.0,
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| 58 |
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"len_pen": 1.0,
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| 59 |
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"accuracy_w2": 0.01,
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| 60 |
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"len_pen2": 1.0,
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"threshold": 0.002,
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| 62 |
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"similarity_fn": "rouge",
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| 63 |
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"acc_scale": "log"
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},
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| 65 |
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"ent_coef": 0.0001,
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| 66 |
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"beta_coef": "0.1",
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| 67 |
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"prompt_0": "{text}",
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| 68 |
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"prompt_1": "{text}\nTL;DR: ",
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| 69 |
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"prompt_2": "Given the text: {role1_output}\nReconstruct the summarized text to the detailed:",
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| 70 |
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"prompt_eval": "{text}\nTL;DR:",
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| 71 |
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"epsilon": 0.2,
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| 72 |
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"a2g_norm": true,
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| 73 |
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"vllm_sleep": true,
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| 74 |
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"lora": false,
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| 75 |
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"need_attn_mask": true,
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| 76 |
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"gamma": 0.95,
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| 77 |
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"trust_remote_code": true,
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| 78 |
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"test_glue": false,
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| 79 |
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"test_clm": false,
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| 80 |
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"causal_model": true,
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| 81 |
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"test_gen": true,
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| 82 |
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"log_rollout_txt": true,
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| 83 |
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"trunc_eval": 20000,
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| 84 |
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"buffer_max_size": 20000,
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| 85 |
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"trunc_evals": [
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| 86 |
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"xsum___20000"
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| 87 |
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],
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| 88 |
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"use_deepspeed": false,
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| 89 |
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"zero_config": 2,
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| 90 |
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"log_interval": "5m",
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| 91 |
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"eval_interval": "2_000",
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| 92 |
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"checkpoint_interval": "2_000",
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| 93 |
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"lm_fraction": -1.0,
|
| 94 |
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"push_to_hub": null,
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| 95 |
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"keep_eval_size": false,
|
| 96 |
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"mixed_precision": "bf16",
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| 97 |
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"tune_metrics": [
|
| 98 |
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"xsum/rouge1___1.0",
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| 99 |
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"xsum/rouge2___2.0",
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| 100 |
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"xsum/bertscore_f1___0.25"
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| 101 |
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],
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| 102 |
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"base_path": "/common/home/users/m/mq.nguyen.2023/testcode/SAC_LM/module9_clmv3",
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| 103 |
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"script": "/common/home/users/m/mq.nguyen.2023/testcode/SAC_LM/module9_clmv3/execute/role_ablation/role_ablation.py",
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| 104 |
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"train_from_raw": true,
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| 105 |
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"world_size": 1,
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| 106 |
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"cpu_per_worker": 6,
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| 107 |
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"gpu_per_worker": 1,
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| 108 |
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"effective_batch_size": 16,
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| 109 |
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"text_col": "text",
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| 110 |
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"_scenario": "clamp_sft_ref",
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| 111 |
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"_dataset": "xsum"
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}
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vocab.json
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