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 4270, 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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| 4278 |
"mean_token_accuracy": 0.7473356157541275,
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"num_tokens": 19839462.0,
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"step": 4260
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}
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],
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| 4283 |
"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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| 4301 |
"train_batch_size": 4,
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| 4302 |
"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": 0.9109333333333334,
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"eval_steps": 500,
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"global_step": 4270,
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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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| 4278 |
"mean_token_accuracy": 0.7473356157541275,
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| 4279 |
"num_tokens": 19839462.0,
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| 4280 |
"step": 4260
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| 4281 |
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},
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| 4282 |
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{
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| 4283 |
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"entropy": 1.0092505671083927,
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| 4284 |
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"epoch": 0.9109333333333334,
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| 4285 |
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"grad_norm": 0.23689568042755127,
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| 4286 |
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"learning_rate": 5.978421984431959e-05,
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| 4287 |
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"loss": 1.110377597808838,
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| 4288 |
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"mean_token_accuracy": 0.7536325603723526,
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| 4289 |
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"num_tokens": 19888786.0,
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| 4290 |
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"step": 4270
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| 4291 |
}
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| 4292 |
],
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| 4293 |
"logging_steps": 10,
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"attributes": {}
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}
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| 4309 |
},
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"total_flos": 9.412431815480525e+16,
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| 4311 |
"train_batch_size": 4,
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| 4312 |
"trial_name": null,
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| 4313 |
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