Instructions to use prxy5608/baa9b3e9-6814-4768-b4bc-00f064231908 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use prxy5608/baa9b3e9-6814-4768-b4bc-00f064231908 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/Qwen2-7B-Instruct") model = PeftModel.from_pretrained(base_model, "prxy5608/baa9b3e9-6814-4768-b4bc-00f064231908") - Notebooks
- Google Colab
- Kaggle
Training in progress, step 27, checkpoint
Browse files
last-checkpoint/adapter_model.safetensors
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last-checkpoint/optimizer.pt
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last-checkpoint/rng_state.pth
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last-checkpoint/scheduler.pt
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last-checkpoint/trainer_state.json
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{
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"best_metric": 1.940207600593567,
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"best_model_checkpoint": "miner_id_24/checkpoint-25",
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"epoch":
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"eval_steps": 25,
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"global_step":
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"is_world_process_zero": true,
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"eval_samples_per_second": 15.602,
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"eval_steps_per_second": 2.035,
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"step": 25
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"logging_steps": 1,
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"should_evaluate": false,
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"should_log": false,
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"should_save": true,
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"should_training_stop":
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"attributes": {}
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"total_flos": 2.
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"train_batch_size": 8,
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"best_metric": 1.940207600593567,
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"best_model_checkpoint": "miner_id_24/checkpoint-25",
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"epoch": 1.0,
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"eval_steps": 25,
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"global_step": 27,
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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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"eval_samples_per_second": 15.602,
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"eval_steps_per_second": 2.035,
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"step": 25
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},
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{
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"epoch": 0.9629629629629629,
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"grad_norm": 1.2259421348571777,
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"learning_rate": 5.089279059533658e-07,
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"loss": 1.9491,
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"step": 26
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},
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{
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"epoch": 1.0,
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"grad_norm": 1.2239744663238525,
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"learning_rate": 0.0,
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"loss": 1.9371,
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"step": 27
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"logging_steps": 1,
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"should_evaluate": false,
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"should_save": true,
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"should_training_stop": true
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"attributes": {}
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"total_flos": 2.468309889712128e+16,
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"train_batch_size": 8,
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