---
library_name: transformers
tags: []
---

# Model Card for Model ID

<!-- Provide a quick summary of what the model is/does. -->
```
2024-10-21 19:23:08,690 - Step: 750, Logs: {'loss': 1.2271, 'grad_norm': 0.06456532329320908, 'learning_rate': 1.5980608369412908e-05, 'epoch': 125.0, 'step': 750}
2024-10-21 19:23:08,690 - Training Loss: 1.2271
2024-10-21 19:23:27,835 - Step: 750, Logs: {'eval_loss': 1.2934688329696655, 'eval_runtime': 19.1422, 'eval_samples_per_second': 11.911, 'eval_steps_per_second': 1.515, 'epoch': 125.0, 'step': 750}
2024-10-21 19:23:27,835 - Validation Loss: 1.2934688329696655
2024-10-21 19:37:47,810 - Step: 800, Logs: {'loss': 1.214, 'grad_norm': 0.06403172016143799, 'learning_rate': 1.469888811684324e-05, 'epoch': 133.33333333333334, 'step': 800}
2024-10-21 19:37:47,810 - Training Loss: 1.214
2024-10-21 19:38:06,951 - Step: 800, Logs: {'eval_loss': 1.2932325601577759, 'eval_runtime': 19.1384, 'eval_samples_per_second': 11.913, 'eval_steps_per_second': 1.515, 'epoch': 133.33333333333334, 'step': 800}
2024-10-21 19:38:06,952 - Validation Loss: 1.2932325601577759
2024-10-21 19:52:28,460 - Step: 850, Logs: {'loss': 1.202, 'grad_norm': 0.07221611589193344, 'learning_rate': 1.3308935187709313e-05, 'epoch': 141.66666666666666, 'step': 850}
2024-10-21 19:52:28,461 - Training Loss: 1.202
2024-10-21 19:52:47,610 - Step: 850, Logs: {'eval_loss': 1.2937428951263428, 'eval_runtime': 19.1469, 'eval_samples_per_second': 11.908, 'eval_steps_per_second': 1.515, 'epoch': 141.66666666666666, 'step': 850}
2024-10-21 19:52:47,610 - Validation Loss: 1.2937428951263428
2024-10-21 20:07:07,416 - Step: 900, Logs: {'loss': 1.1901, 'grad_norm': 0.08854028582572937, 'learning_rate': 1.1842765310429778e-05, 'epoch': 150.0, 'step': 900}
2024-10-21 20:07:07,416 - Training Loss: 1.1901
2024-10-21 20:07:26,555 - Step: 900, Logs: {'eval_loss': 1.2950921058654785, 'eval_runtime': 19.136, 'eval_samples_per_second': 11.915, 'eval_steps_per_second': 1.515, 'epoch': 150.0, 'step': 900}
2024-10-21 20:07:26,555 - Validation Loss: 1.2950921058654785
2024-10-21 20:11:30,601 - Total training time: 3764.0017805099487 seconds
```

![image/png](https://cdn-uploads.huggingface.co/production/uploads/663ce15f197afc063058dc3a/gMbzxNWZ7nr1YhkXvguj7.png)
![image/png](https://cdn-uploads.huggingface.co/production/uploads/663ce15f197afc063058dc3a/jymYaBPf_Am1hlQp0f8cZ.png)
![image/png](https://cdn-uploads.huggingface.co/production/uploads/663ce15f197afc063058dc3a/rSIRY2iT99OTMMX8tHJ3M.png)
![image/png](https://cdn-uploads.huggingface.co/production/uploads/663ce15f197afc063058dc3a/2Sj9eqafjRnaNIk81jXcg.png)
![image/png](https://cdn-uploads.huggingface.co/production/uploads/663ce15f197afc063058dc3a/fL5yRVLC_6WtHvORpQb4B.png)
![image/png](https://cdn-uploads.huggingface.co/production/uploads/663ce15f197afc063058dc3a/qBBnWtKEXPuua8JKKAWDB.png)
![image/png](https://cdn-uploads.huggingface.co/production/uploads/663ce15f197afc063058dc3a/XU0NzYpKu1rkppTZihdZ5.png)
![image/png](https://cdn-uploads.huggingface.co/production/uploads/663ce15f197afc063058dc3a/d_H9k2LPj45HOWzNuUSvs.png)
![image/png](https://cdn-uploads.huggingface.co/production/uploads/663ce15f197afc063058dc3a/AVH-uloSwMJ0K2tgHaSRj.png)

## Model Details

### Model Description

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This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.

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### Model Sources [optional]

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## Uses

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### Direct Use

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### Out-of-Scope Use

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## Bias, Risks, and Limitations

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### Recommendations

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Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.

## How to Get Started with the Model

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## Training Details

### Training Data

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### Training Procedure

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#### Preprocessing [optional]

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#### Training Hyperparameters

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#### Speeds, Sizes, Times [optional]

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## Evaluation

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### Testing Data, Factors & Metrics

#### Testing Data

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#### Metrics

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### Results

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#### Summary



## Model Examination [optional]

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## Environmental Impact

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Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).

- **Hardware Type:** [More Information Needed]
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## Technical Specifications [optional]

### Model Architecture and Objective

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### Compute Infrastructure

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## Glossary [optional]

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