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 1810, 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": 0.7640544638037682,
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"step": 1800
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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": 3.
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"train_batch_size": 4,
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"trial_name": null,
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"best_global_step": null,
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"epoch": 0.38613333333333333,
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"global_step": 1810,
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"is_local_process_zero": true,
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"is_world_process_zero": true,
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| 1818 |
"mean_token_accuracy": 0.7640544638037682,
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| 1819 |
"num_tokens": 8346150.0,
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"step": 1800
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{
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"entropy": 0.960440730303526,
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"grad_norm": 0.2441101223230362,
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"learning_rate": 9.333296506763505e-05,
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"loss": 1.059675121307373,
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"mean_token_accuracy": 0.7603183135390281,
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| 1829 |
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"num_tokens": 8393408.0,
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| 1830 |
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"step": 1810
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| 1831 |
}
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],
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"logging_steps": 10,
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"attributes": {}
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}
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"total_flos": 3.988529611626394e+16,
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"train_batch_size": 4,
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