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 4140, 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": 0.771124804764986,
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"num_tokens": 19252396.0,
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"step": 4130
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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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| 4171 |
"train_batch_size": 4,
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| 4172 |
"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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"epoch": 0.8832,
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"eval_steps": 500,
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"global_step": 4140,
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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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| 4148 |
"mean_token_accuracy": 0.771124804764986,
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| 4149 |
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| 4150 |
"step": 4130
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| 4152 |
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{
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| 4153 |
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"entropy": 0.7921540692448616,
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| 4154 |
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"epoch": 0.8832,
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| 4155 |
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"grad_norm": 0.3147003650665283,
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| 4156 |
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"learning_rate": 6.198000166408651e-05,
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| 4157 |
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"loss": 0.8609647750854492,
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| 4158 |
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"mean_token_accuracy": 0.7940000563859939,
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| 4159 |
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"num_tokens": 19293212.0,
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| 4160 |
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"step": 4140
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| 4161 |
}
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| 4162 |
],
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| 4163 |
"logging_steps": 10,
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| 4177 |
"attributes": {}
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}
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| 4180 |
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"total_flos": 9.128628244888166e+16,
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| 4181 |
"train_batch_size": 4,
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| 4183 |
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