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 4190, 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": 0.780048543214798,
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"num_tokens": 19476928.0,
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"step": 4180
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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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| 4221 |
"train_batch_size": 4,
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"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": 0.8938666666666667,
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"eval_steps": 500,
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"global_step": 4190,
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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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| 4198 |
"mean_token_accuracy": 0.780048543214798,
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| 4199 |
"num_tokens": 19476928.0,
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| 4200 |
"step": 4180
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{
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| 4203 |
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"entropy": 0.9338957525789737,
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| 4204 |
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"epoch": 0.8938666666666667,
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| 4205 |
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"grad_norm": 0.3184056282043457,
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| 4206 |
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"learning_rate": 6.113809865554853e-05,
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| 4207 |
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"loss": 1.0237668991088866,
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| 4208 |
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"mean_token_accuracy": 0.7652892589569091,
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| 4209 |
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"num_tokens": 19522534.0,
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| 4210 |
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"step": 4190
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| 4211 |
}
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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": 9.23705904874967e+16,
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| 4231 |
"train_batch_size": 4,
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"trial_name": null,
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