Instructions to use surakarteh/c59b5744-9a83-446c-a62b-e03e3146f75b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use surakarteh/c59b5744-9a83-446c-a62b-e03e3146f75b with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("elyza/Llama-3-ELYZA-JP-8B") model = PeftModel.from_pretrained(base_model, "surakarteh/c59b5744-9a83-446c-a62b-e03e3146f75b") - Notebooks
- Google Colab
- Kaggle
Training in progress, step 625, 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": 0.039619311690330505,
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"best_model_checkpoint": "miner_id_24/checkpoint-500",
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"epoch": 0.
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"eval_steps": 500,
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"global_step":
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"is_world_process_zero": true,
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"eval_samples_per_second": 15.021,
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"eval_steps_per_second": 3.011,
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"step": 500
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"logging_steps": 50,
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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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"train_batch_size": 5,
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"epoch": 0.9133421014175069,
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"global_step": 625,
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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": 15.021,
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"eval_steps_per_second": 3.011,
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"step": 500
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{
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"epoch": 0.8037410492474061,
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"grad_norm": 0.11217395961284637,
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"learning_rate": 1.45506290208529e-05,
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"loss": 0.0382,
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"step": 550
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{
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"grad_norm": 0.057221416383981705,
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"learning_rate": 1.6436065305491224e-06,
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"logging_steps": 50,
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"should_evaluate": false,
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"should_training_stop": true
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