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 4050, 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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| 4058 |
"mean_token_accuracy": 0.7643599301576615,
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"num_tokens": 18843087.0,
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| 4060 |
"step": 4040
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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": 8.
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| 4081 |
"train_batch_size": 4,
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| 4082 |
"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": 0.864,
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"eval_steps": 500,
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"global_step": 4050,
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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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| 4058 |
"mean_token_accuracy": 0.7643599301576615,
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| 4059 |
"num_tokens": 18843087.0,
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| 4060 |
"step": 4040
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| 4061 |
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| 4062 |
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{
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| 4063 |
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"entropy": 0.9580571033060551,
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| 4064 |
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"epoch": 0.864,
|
| 4065 |
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"grad_norm": 0.2631727159023285,
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| 4066 |
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"learning_rate": 6.348621561803495e-05,
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| 4067 |
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"loss": 1.0001374244689942,
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| 4068 |
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"mean_token_accuracy": 0.7608293548226357,
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| 4069 |
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"num_tokens": 18891900.0,
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| 4070 |
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"step": 4050
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| 4071 |
}
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| 4072 |
],
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| 4073 |
"logging_steps": 10,
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| 4087 |
"attributes": {}
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| 4088 |
}
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| 4089 |
},
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| 4090 |
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"total_flos": 8.946135200719565e+16,
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| 4091 |
"train_batch_size": 4,
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| 4092 |
"trial_name": null,
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| 4093 |
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