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 3910, 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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| 3918 |
"mean_token_accuracy": 0.7520590081810952,
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"num_tokens": 18184374.0,
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| 3920 |
"step": 3900
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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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| 3941 |
"train_batch_size": 4,
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| 3942 |
"trial_name": null,
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| 3943 |
"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": 0.8341333333333333,
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"eval_steps": 500,
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| 7 |
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"global_step": 3910,
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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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| 3918 |
"mean_token_accuracy": 0.7520590081810952,
|
| 3919 |
"num_tokens": 18184374.0,
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| 3920 |
"step": 3900
|
| 3921 |
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},
|
| 3922 |
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{
|
| 3923 |
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"entropy": 1.0141760632395744,
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| 3924 |
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"epoch": 0.8341333333333333,
|
| 3925 |
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"grad_norm": 0.29730224609375,
|
| 3926 |
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"learning_rate": 6.580266813050187e-05,
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| 3927 |
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"loss": 1.107116985321045,
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| 3928 |
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"mean_token_accuracy": 0.7563492476940155,
|
| 3929 |
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"num_tokens": 18226039.0,
|
| 3930 |
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"step": 3910
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| 3931 |
}
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| 3932 |
],
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| 3933 |
"logging_steps": 10,
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| 3947 |
"attributes": {}
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| 3948 |
}
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| 3949 |
},
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| 3950 |
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"total_flos": 8.627964868946534e+16,
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| 3951 |
"train_batch_size": 4,
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"trial_name": null,
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| 3953 |
"trial_params": null
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