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---
library_name: transformers
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: eo_train1-10_eval11
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# eo_train1-10_eval11
This model is a fine-tuned version of [](https://huggingface.co/) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6932
- Accuracy: 0.5
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 0.001
- train_batch_size: 128
- eval_batch_size: 128
- seed: 7658372
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- training_steps: 3000
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| No log | 0 | 0 | 2.6863 | 0.0 |
| 0.6284 | 100.0 | 100 | 0.7859 | 0.5 |
| 0.548 | 200.0 | 200 | 0.7353 | 0.5 |
| 0.5022 | 300.0 | 300 | 0.6964 | 0.5 |
| 0.6935 | 400.0 | 400 | 0.6936 | 0.5 |
| 0.6933 | 500.0 | 500 | 0.6933 | 0.5 |
| 0.6932 | 600.0 | 600 | 0.6932 | 0.5 |
| 0.6932 | 700.0 | 700 | 0.6932 | 0.5 |
| 0.6932 | 800.0 | 800 | 0.6932 | 0.5 |
| 0.6932 | 900.0 | 900 | 0.6932 | 0.5 |
| 0.6932 | 1000.0 | 1000 | 0.6932 | 0.5 |
| 0.6932 | 1100.0 | 1100 | 0.6932 | 0.5 |
| 0.6932 | 1200.0 | 1200 | 0.6932 | 0.5 |
| 0.6932 | 1300.0 | 1300 | 0.6932 | 0.5 |
| 0.6932 | 1400.0 | 1400 | 0.6932 | 0.5 |
| 0.6932 | 1500.0 | 1500 | 0.6932 | 0.5 |
| 0.6932 | 1600.0 | 1600 | 0.6932 | 0.5 |
| 0.6932 | 1700.0 | 1700 | 0.6932 | 0.5 |
| 0.6932 | 1800.0 | 1800 | 0.6932 | 0.5 |
| 0.6932 | 1900.0 | 1900 | 0.6932 | 0.5 |
| 0.6932 | 2000.0 | 2000 | 0.6932 | 0.5 |
| 0.6932 | 2100.0 | 2100 | 0.6932 | 0.5 |
| 0.6932 | 2200.0 | 2200 | 0.6932 | 0.5 |
| 0.6932 | 2300.0 | 2300 | 0.6932 | 0.5 |
| 0.6932 | 2400.0 | 2400 | 0.6932 | 0.5 |
| 0.6932 | 2500.0 | 2500 | 0.6932 | 0.5 |
| 0.6932 | 2600.0 | 2600 | 0.6932 | 0.5 |
| 0.6932 | 2700.0 | 2700 | 0.6932 | 0.5 |
| 0.6932 | 2800.0 | 2800 | 0.6932 | 0.5 |
| 0.6932 | 2900.0 | 2900 | 0.6932 | 0.5 |
| 0.6932 | 3000.0 | 3000 | 0.6932 | 0.5 |
### Framework versions
- Transformers 4.46.0
- Pytorch 2.5.1
- Datasets 3.1.0
- Tokenizers 0.20.1
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