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 4080, 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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| 4088 |
"mean_token_accuracy": 0.7691247522830963,
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"num_tokens": 18984144.0,
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| 4090 |
"step": 4070
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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":
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| 4111 |
"train_batch_size": 4,
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| 4112 |
"trial_name": null,
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| 4113 |
"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": 0.8704,
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"eval_steps": 500,
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"global_step": 4080,
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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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| 4088 |
"mean_token_accuracy": 0.7691247522830963,
|
| 4089 |
"num_tokens": 18984144.0,
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| 4090 |
"step": 4070
|
| 4091 |
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},
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| 4092 |
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{
|
| 4093 |
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"entropy": 0.9895228892564774,
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| 4094 |
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"epoch": 0.8704,
|
| 4095 |
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"grad_norm": 0.2775322198867798,
|
| 4096 |
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"learning_rate": 6.298552651371316e-05,
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| 4097 |
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"loss": 1.10516300201416,
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| 4098 |
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"mean_token_accuracy": 0.7543898217380047,
|
| 4099 |
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"num_tokens": 19027278.0,
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| 4100 |
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"step": 4080
|
| 4101 |
}
|
| 4102 |
],
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| 4103 |
"logging_steps": 10,
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| 4117 |
"attributes": {}
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| 4118 |
}
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| 4119 |
},
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| 4120 |
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"total_flos": 9.007989062536704e+16,
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| 4121 |
"train_batch_size": 4,
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| 4122 |
"trial_name": null,
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| 4123 |
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