README.md

---
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: TED_CLM_gpt2_tedlium6
  results: []
---

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# TED_CLM_gpt2_tedlium6

This model is a fine-tuned version of [Lakoc/TED_CLM_gpt2_tedlium4](https://huggingface.co/Lakoc/TED_CLM_gpt2_tedlium4) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.8904
- Accuracy: 0.5555

## 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: 0.005
- train_batch_size: 128
- eval_batch_size: 128
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- total_train_batch_size: 512
- total_eval_batch_size: 512
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 15.0

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.7738        | 1.0   | 180  | 1.8841          | 0.5533   |
| 1.7249        | 2.0   | 360  | 1.8786          | 0.5550   |
| 1.6667        | 3.0   | 540  | 1.8845          | 0.5548   |
| 1.6369        | 4.0   | 720  | 1.8904          | 0.5555   |
| 1.6309        | 5.0   | 900  | 1.8904          | 0.5555   |
| 1.6288        | 6.0   | 1080 | 1.8904          | 0.5555   |
| 1.6277        | 7.0   | 1260 | 1.8904          | 0.5555   |


### Framework versions

- Transformers 4.31.0.dev0
- Pytorch 2.1.0+cu121
- Datasets 2.13.1
- Tokenizers 0.13.3