Instructions to use tuanna08go/dbf1257f-984b-4518-b654-372d08f639ed with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use tuanna08go/dbf1257f-984b-4518-b654-372d08f639ed with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/tinyllama-chat") model = PeftModel.from_pretrained(base_model, "tuanna08go/dbf1257f-984b-4518-b654-372d08f639ed") - Notebooks
- Google Colab
- Kaggle
Training in progress, step 18, 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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"is_world_process_zero": true,
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"eval_samples_per_second": 37.967,
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"eval_steps_per_second": 4.979,
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"step": 12
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"logging_steps": 10,
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"should_evaluate": false,
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"should_training_stop":
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"total_flos": 1.
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"train_batch_size": 8,
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"trial_params": null
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"global_step": 18,
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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": 37.967,
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"eval_steps_per_second": 4.979,
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"step": 12
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{
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"epoch": 0.8888888888888888,
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"eval_loss": 0.49720510840415955,
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"eval_runtime": 3.2217,
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"eval_samples_per_second": 37.868,
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"eval_steps_per_second": 4.966,
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"step": 16
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"logging_steps": 10,
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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": true
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"attributes": {}
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"total_flos": 1.4720828348301312e+16,
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"train_batch_size": 8,
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"trial_name": null,
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