Instructions to use moos124/code-reasoning-0.5b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use moos124/code-reasoning-0.5b with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("moos124/code-reasoning-0.5b", dtype="auto") - Notebooks
- Google Colab
- Kaggle
Training in progress, step 4310, 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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"best_global_step": null,
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"best_metric": null,
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"best_model_checkpoint": null,
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"epoch": 0.
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"eval_steps": 500,
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"global_step":
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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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"mean_token_accuracy": 0.7699793577194214,
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"num_tokens": 20021630.0,
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"step": 4300
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}
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],
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"logging_steps": 10,
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"attributes": {}
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}
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},
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"total_flos": 9.
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| 4341 |
"train_batch_size": 4,
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"trial_name": null,
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"best_global_step": null,
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"best_metric": null,
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"epoch": 0.9194666666666667,
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"global_step": 4310,
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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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| 4318 |
"mean_token_accuracy": 0.7699793577194214,
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| 4319 |
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| 4320 |
"step": 4300
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{
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| 4323 |
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"entropy": 0.930675259232521,
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| 4324 |
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"epoch": 0.9194666666666667,
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| 4325 |
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"grad_norm": 0.23214256763458252,
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| 4326 |
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"learning_rate": 5.9104401994242786e-05,
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| 4327 |
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"loss": 1.0291691780090333,
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"mean_token_accuracy": 0.7654816180467605,
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| 4329 |
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"num_tokens": 20070846.0,
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| 4330 |
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"step": 4310
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| 4331 |
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| 4332 |
],
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"logging_steps": 10,
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"attributes": {}
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}
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"total_flos": 9.49961984250839e+16,
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| 4351 |
"train_batch_size": 4,
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"trial_name": null,
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