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 3190, 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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| 3198 |
"mean_token_accuracy": 0.7741461530327797,
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"num_tokens": 14803777.0,
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| 3200 |
"step": 3180
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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": 7.
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| 3221 |
"train_batch_size": 4,
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| 3222 |
"trial_name": null,
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| 3223 |
"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": 0.6805333333333333,
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"eval_steps": 500,
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"global_step": 3190,
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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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| 3198 |
"mean_token_accuracy": 0.7741461530327797,
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| 3199 |
"num_tokens": 14803777.0,
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| 3200 |
"step": 3180
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| 3201 |
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},
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| 3202 |
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{
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| 3203 |
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"entropy": 0.9152800880372525,
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| 3204 |
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"epoch": 0.6805333333333333,
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| 3205 |
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"grad_norm": 0.25680598616600037,
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| 3206 |
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"learning_rate": 7.701483169861713e-05,
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| 3207 |
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"loss": 0.9781417846679688,
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| 3208 |
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"mean_token_accuracy": 0.7678594440221786,
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| 3209 |
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"num_tokens": 14851182.0,
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| 3210 |
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"step": 3190
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| 3211 |
}
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| 3212 |
],
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| 3213 |
"logging_steps": 10,
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"attributes": {}
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}
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| 3230 |
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"total_flos": 7.033748178319258e+16,
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| 3231 |
"train_batch_size": 4,
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"trial_name": null,
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