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 1170, 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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| 1178 |
"mean_token_accuracy": 0.7714703544974327,
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"num_tokens": 5393421.0,
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"step": 1160
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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": 2.
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| 1201 |
"train_batch_size": 4,
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| 1202 |
"trial_name": null,
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| 1203 |
"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": 0.2496,
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"eval_steps": 500,
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"global_step": 1170,
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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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| 1178 |
"mean_token_accuracy": 0.7714703544974327,
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| 1179 |
"num_tokens": 5393421.0,
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| 1180 |
"step": 1160
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| 1181 |
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},
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| 1182 |
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{
|
| 1183 |
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"entropy": 1.0325972460210324,
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| 1184 |
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"epoch": 0.2496,
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| 1185 |
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"grad_norm": 0.26943519711494446,
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| 1186 |
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"learning_rate": 9.775501575939227e-05,
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| 1187 |
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"loss": 1.0748598098754882,
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| 1188 |
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"mean_token_accuracy": 0.7444046661257744,
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| 1189 |
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"num_tokens": 5443639.0,
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| 1190 |
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"step": 1170
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| 1191 |
}
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| 1192 |
],
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| 1193 |
"logging_steps": 10,
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| 1207 |
"attributes": {}
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| 1208 |
}
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},
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| 1210 |
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"total_flos": 2.577578282312909e+16,
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| 1211 |
"train_batch_size": 4,
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"trial_name": null,
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"trial_params": null
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