Instructions to use mbruton/gal_en_mBERT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mbruton/gal_en_mBERT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="mbruton/gal_en_mBERT")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("mbruton/gal_en_mBERT") model = AutoModelForTokenClassification.from_pretrained("mbruton/gal_en_mBERT", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Upload 11 files
Browse files- config.json +135 -0
- optimizer.pt +3 -0
- pytorch_model.bin +3 -0
- rng_state.pth +3 -0
- scheduler.pt +3 -0
- special_tokens_map.json +7 -0
- tokenizer.json +0 -0
- tokenizer_config.json +15 -0
- trainer_state.json +106 -0
- training_args.bin +3 -0
- vocab.txt +0 -0
config.json
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{
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"_name_or_path": "liaad/srl-en_mbert-base",
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"architectures": [
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"BertForTokenClassification"
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],
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"attention_probs_dropout_prob": 0.1,
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"classifier_dropout": null,
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"directionality": "bidi",
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"hidden_act": "gelu",
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"hidden_dropout_prob": 0.1,
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"hidden_size": 768,
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"id2label": {
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"0": "O",
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"1": "r0:arg0",
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"2": "r0:arg1",
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"3": "r0:arg2",
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"4": "r0:root",
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"5": "r10:arg0",
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"6": "r10:arg1",
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"7": "r10:root",
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"8": "r11:arg0",
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"9": "r11:root",
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"10": "r12:arg1",
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"11": "r12:root",
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"12": "r13:arg1",
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"13": "r13:root",
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"14": "r1:arg0",
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"15": "r1:arg1",
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"16": "r1:arg2",
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"17": "r1:root",
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"18": "r2:arg0",
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"19": "r2:arg1",
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"20": "r2:arg2",
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"21": "r2:root",
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"22": "r3:arg0",
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"23": "r3:arg1",
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"24": "r3:arg2",
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"25": "r3:root",
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"26": "r4:arg0",
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"27": "r4:arg1",
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"28": "r4:arg2",
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"29": "r4:root",
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"30": "r5:arg0",
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"31": "r5:arg1",
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"32": "r5:arg2",
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"33": "r5:root",
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"34": "r6:arg0",
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"35": "r6:arg1",
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"36": "r6:arg2",
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"37": "r6:root",
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"38": "r7:arg0",
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"39": "r7:arg1",
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"40": "r7:arg2",
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"41": "r7:root",
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"42": "r8:arg0",
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"43": "r8:arg1",
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"44": "r8:arg2",
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"45": "r8:root",
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"46": "r9:arg0",
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"47": "r9:arg1",
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"48": "r9:arg2",
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"49": "r9:root"
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},
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"initializer_range": 0.02,
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"intermediate_size": 3072,
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"label2id": {
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"O": 0,
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"r0:arg0": 1,
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"r0:arg1": 2,
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"r0:arg2": 3,
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"r0:root": 4,
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"r10:arg0": 5,
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"r10:arg1": 6,
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"r10:root": 7,
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"r11:arg0": 8,
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"r11:root": 9,
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"r12:arg1": 10,
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"r12:root": 11,
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"r13:arg1": 12,
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"r13:root": 13,
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"r1:arg0": 14,
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"r1:arg1": 15,
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"r1:arg2": 16,
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"r1:root": 17,
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"r2:arg0": 18,
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"r2:arg1": 19,
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"r2:arg2": 20,
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"r2:root": 21,
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"r3:arg0": 22,
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"r3:arg1": 23,
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"r3:arg2": 24,
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"r3:root": 25,
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"r4:arg0": 26,
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"r4:arg1": 27,
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"r4:arg2": 28,
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"r4:root": 29,
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"r5:arg0": 30,
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"r5:arg1": 31,
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"r5:arg2": 32,
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"r5:root": 33,
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"r6:arg0": 34,
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"r6:arg1": 35,
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"r6:arg2": 36,
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"r6:root": 37,
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"r7:arg0": 38,
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"r7:arg1": 39,
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"r7:arg2": 40,
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"r7:root": 41,
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"r8:arg0": 42,
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"r8:arg1": 43,
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"r8:arg2": 44,
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"r8:root": 45,
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"r9:arg0": 46,
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"r9:arg1": 47,
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"r9:arg2": 48,
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"r9:root": 49
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},
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"layer_norm_eps": 1e-12,
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"max_position_embeddings": 512,
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"model_type": "bert",
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"num_attention_heads": 12,
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"num_hidden_layers": 12,
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"pad_token_id": 0,
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"pooler_fc_size": 768,
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"pooler_num_attention_heads": 12,
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"pooler_num_fc_layers": 3,
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"pooler_size_per_head": 128,
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"pooler_type": "first_token_transform",
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"position_embedding_type": "absolute",
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"torch_dtype": "float32",
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"transformers_version": "4.27.4",
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"type_vocab_size": 2,
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"use_cache": true,
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"vocab_size": 119547
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}
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optimizer.pt
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version https://git-lfs.github.com/spec/v1
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oid sha256:c5d8973f363cfc6d8de8d44368d7778f6dbe6e2b079346fcea0c455397c2576e
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size 1418525797
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pytorch_model.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:c40bb8048ab950c5b3507fcdf9863a438f3268ec23662eafe8a9be7dfab0d872
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size 709275633
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rng_state.pth
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version https://git-lfs.github.com/spec/v1
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oid sha256:28238529fef29fb763aa58326402157c5346334cabb7c711b05d5a3f1e020c9e
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size 14503
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scheduler.pt
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version https://git-lfs.github.com/spec/v1
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oid sha256:b14881f8352737c801b7e15ff2544419ace05937680ded1c03cfe4be45005e78
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size 623
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special_tokens_map.json
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{
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"cls_token": "[CLS]",
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"mask_token": "[MASK]",
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"pad_token": "[PAD]",
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"sep_token": "[SEP]",
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"unk_token": "[UNK]"
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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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"cls_token": "[CLS]",
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"do_basic_tokenize": true,
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"do_lower_case": false,
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"mask_token": "[MASK]",
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"model_max_length": 512,
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"never_split": null,
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"pad_token": "[PAD]",
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"sep_token": "[SEP]",
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"special_tokens_map_file": "/root/.cache/huggingface/hub/models--liaad--srl-en_mbert-base/snapshots/0c963b783ca3a81aafce1c53c0bb17715a7f0903/special_tokens_map.json",
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"strip_accents": null,
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"tokenize_chinese_chars": true,
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"tokenizer_class": "BertTokenizer",
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"unk_token": "[UNK]"
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}
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trainer_state.json
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{
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"best_metric": 0.3187411427497864,
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"best_model_checkpoint": "gal_en_mBERT/checkpoint-1250",
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"epoch": 6.0,
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"global_step": 1500,
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"is_hyper_param_search": false,
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"is_local_process_zero": true,
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"is_world_process_zero": true,
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"log_history": [
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{
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"epoch": 1.0,
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| 12 |
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"eval_accuracy": 0.8779133954857704,
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"eval_f1": 0.5262912258867455,
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"eval_loss": 0.44472846388816833,
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| 15 |
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"eval_precision": 0.5704890387858348,
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| 16 |
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"eval_recall": 0.4884493213976321,
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| 17 |
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"eval_runtime": 5.3275,
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| 18 |
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"eval_samples_per_second": 187.141,
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| 19 |
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"eval_steps_per_second": 11.825,
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| 20 |
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"step": 250
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},
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{
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"epoch": 2.0,
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"learning_rate": 1.9600000000000002e-05,
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"loss": 0.5654,
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| 26 |
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"step": 500
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},
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{
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| 29 |
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"epoch": 2.0,
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| 30 |
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"eval_accuracy": 0.897479146221786,
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| 31 |
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"eval_f1": 0.6228456315750205,
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| 32 |
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"eval_loss": 0.36001163721084595,
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| 33 |
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"eval_precision": 0.6444341516134012,
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| 34 |
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"eval_recall": 0.6026566560785446,
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| 35 |
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"eval_runtime": 5.2617,
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| 36 |
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"eval_samples_per_second": 189.481,
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| 37 |
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"eval_steps_per_second": 11.973,
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"step": 500
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},
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{
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| 41 |
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"epoch": 3.0,
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| 42 |
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"eval_accuracy": 0.9003312070657508,
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| 43 |
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"eval_f1": 0.6522937725312786,
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| 44 |
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"eval_loss": 0.3470691740512848,
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| 45 |
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"eval_precision": 0.6389696717906107,
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| 46 |
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"eval_recall": 0.666185388391568,
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| 47 |
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"eval_runtime": 5.3516,
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| 48 |
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"eval_samples_per_second": 186.3,
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| 49 |
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| 70 |
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| 87 |
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| 88 |
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training_args.bin
ADDED
|
@@ -0,0 +1,3 @@
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|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
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| 2 |
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oid sha256:999e47d0e57ea1a36c9092deb6b1fe05b1351f5189bf370df1e0c1d68c5798a6
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| 3 |
+
size 3503
|
vocab.txt
ADDED
|
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