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 3480, 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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| 3488 |
"mean_token_accuracy": 0.7686163082718849,
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"num_tokens": 16169199.0,
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| 3490 |
"step": 3470
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}
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],
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| 3493 |
"logging_steps": 10,
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"attributes": {}
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}
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},
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"total_flos": 7.
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| 3511 |
"train_batch_size": 4,
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| 3512 |
"trial_name": null,
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"trial_params": null
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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": 0.7424,
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"eval_steps": 500,
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"global_step": 3480,
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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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| 3488 |
"mean_token_accuracy": 0.7686163082718849,
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| 3489 |
"num_tokens": 16169199.0,
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| 3490 |
"step": 3470
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| 3491 |
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},
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| 3492 |
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{
|
| 3493 |
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"entropy": 1.089708861708641,
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| 3494 |
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"epoch": 0.7424,
|
| 3495 |
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"grad_norm": 0.2787526547908783,
|
| 3496 |
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"learning_rate": 7.266250729213105e-05,
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| 3497 |
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"loss": 1.177119255065918,
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| 3498 |
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"mean_token_accuracy": 0.7344872549176216,
|
| 3499 |
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"num_tokens": 16218140.0,
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| 3500 |
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"step": 3480
|
| 3501 |
}
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| 3502 |
],
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| 3503 |
"logging_steps": 10,
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| 3517 |
"attributes": {}
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| 3518 |
}
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| 3519 |
},
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| 3520 |
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"total_flos": 7.682752319723213e+16,
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| 3521 |
"train_batch_size": 4,
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| 3522 |
"trial_name": null,
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| 3523 |
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