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 3940, 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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| 3948 |
"mean_token_accuracy": 0.767199169844389,
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| 3949 |
"num_tokens": 18314733.0,
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| 3950 |
"step": 3930
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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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| 3971 |
"train_batch_size": 4,
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| 3972 |
"trial_name": null,
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| 3973 |
"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": 0.8405333333333334,
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"eval_steps": 500,
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"global_step": 3940,
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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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| 3948 |
"mean_token_accuracy": 0.767199169844389,
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| 3949 |
"num_tokens": 18314733.0,
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| 3950 |
"step": 3930
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| 3951 |
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},
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| 3952 |
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{
|
| 3953 |
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"entropy": 0.9812062717974186,
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| 3954 |
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"epoch": 0.8405333333333334,
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| 3955 |
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"grad_norm": 0.2531512677669525,
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| 3956 |
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"learning_rate": 6.530922485470531e-05,
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| 3957 |
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"loss": 1.0596059799194335,
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| 3958 |
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"mean_token_accuracy": 0.764385013282299,
|
| 3959 |
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"num_tokens": 18367778.0,
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| 3960 |
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"step": 3940
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| 3961 |
}
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| 3962 |
],
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| 3963 |
"logging_steps": 10,
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| 3977 |
"attributes": {}
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| 3978 |
}
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| 3979 |
},
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| 3980 |
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"total_flos": 8.695267306562765e+16,
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| 3981 |
"train_batch_size": 4,
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| 3982 |
"trial_name": null,
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| 3983 |
"trial_params": null
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