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 2410, 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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| 2418 |
"mean_token_accuracy": 0.7355501770973205,
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"num_tokens": 11167106.0,
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"step": 2400
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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": 5.
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| 2441 |
"train_batch_size": 4,
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| 2442 |
"trial_name": null,
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| 2443 |
"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": 0.5141333333333333,
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"eval_steps": 500,
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"global_step": 2410,
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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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| 2418 |
"mean_token_accuracy": 0.7355501770973205,
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| 2419 |
"num_tokens": 11167106.0,
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| 2420 |
"step": 2400
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| 2421 |
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},
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| 2422 |
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{
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| 2423 |
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"entropy": 0.9723750591278076,
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| 2424 |
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"epoch": 0.5141333333333333,
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| 2425 |
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"grad_norm": 0.3258633315563202,
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| 2426 |
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"learning_rate": 8.725820979735436e-05,
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| 2427 |
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"loss": 1.1157949447631836,
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| 2428 |
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"mean_token_accuracy": 0.7603042379021645,
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| 2429 |
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"num_tokens": 11211815.0,
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| 2430 |
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"step": 2410
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| 2431 |
}
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| 2432 |
],
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| 2433 |
"logging_steps": 10,
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| 2447 |
"attributes": {}
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}
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| 2449 |
},
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| 2450 |
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"total_flos": 5.317580177261875e+16,
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| 2451 |
"train_batch_size": 4,
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| 2452 |
"trial_name": null,
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| 2453 |
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