---
license: apache-2.0
base_model: facebook/wav2vec2-large-xlsr-53
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: wav2vec2-xlsr-53-ft-btb-cy
  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. -->

# wav2vec2-xlsr-53-ft-btb-cy

This model is a fine-tuned version of [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4105
- Wer: 0.3136

## 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: 0.0003
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 2600
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer    |
|:-------------:|:------:|:----:|:---------------:|:------:|
| No log        | 0.1414 | 100  | 3.2195          | 1.0    |
| No log        | 0.2829 | 200  | 3.1180          | 1.0    |
| No log        | 0.4243 | 300  | 1.7236          | 0.9364 |
| No log        | 0.5658 | 400  | 1.1579          | 0.7628 |
| 3.0279        | 0.7072 | 500  | 0.9558          | 0.6721 |
| 3.0279        | 0.8487 | 600  | 0.8189          | 0.6424 |
| 3.0279        | 0.9901 | 700  | 0.6973          | 0.5164 |
| 3.0279        | 1.1315 | 800  | 0.6183          | 0.4752 |
| 3.0279        | 1.2730 | 900  | 0.5936          | 0.4703 |
| 0.7925        | 1.4144 | 1000 | 0.5498          | 0.4304 |
| 0.7925        | 1.5559 | 1100 | 0.5286          | 0.4148 |
| 0.7925        | 1.6973 | 1200 | 0.5130          | 0.3974 |
| 0.7925        | 1.8388 | 1300 | 0.4878          | 0.3864 |
| 0.7925        | 1.9802 | 1400 | 0.4740          | 0.3733 |
| 0.62          | 2.1216 | 1500 | 0.4578          | 0.3593 |
| 0.62          | 2.2631 | 1600 | 0.4535          | 0.3500 |
| 0.62          | 2.4045 | 1700 | 0.4485          | 0.3497 |
| 0.62          | 2.5460 | 1800 | 0.4373          | 0.3431 |
| 0.62          | 2.6874 | 1900 | 0.4362          | 0.3429 |
| 0.4879        | 2.8289 | 2000 | 0.4236          | 0.3327 |
| 0.4879        | 2.9703 | 2100 | 0.4172          | 0.3257 |
| 0.4879        | 3.1117 | 2200 | 0.4206          | 0.3217 |
| 0.4879        | 3.2532 | 2300 | 0.4166          | 0.3199 |
| 0.4879        | 3.3946 | 2400 | 0.4134          | 0.3173 |
| 0.4036        | 3.5361 | 2500 | 0.4110          | 0.3159 |
| 0.4036        | 3.6775 | 2600 | 0.4105          | 0.3136 |


### Framework versions

- Transformers 4.40.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1