---
license: apache-2.0
base_model: facebook/wav2vec2-large-xlsr-53
tags:
- automatic-speech-recognition
- DewiBrynJones/banc-trawsgrifiadau-bangor-clean-with-ccv
- generated_from_trainer
metrics:
- wer
model-index:
- name: wav2vec2-xlsr-53-ft-btb-ccv-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-ccv-cy

This model is a fine-tuned version of [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on the DEWIBRYNJONES/BANC-TRAWSGRIFIADAU-BANGOR-CLEAN-WITH-CCV - DEFAULT dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4200
- Wer: 0.3227

## 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: 64
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 2000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer    |
|:-------------:|:------:|:----:|:---------------:|:------:|
| No log        | 0.1548 | 100  | 3.5623          | 1.0    |
| No log        | 0.3096 | 200  | 3.2967          | 1.0    |
| No log        | 0.4644 | 300  | 2.6484          | 1.0000 |
| No log        | 0.6192 | 400  | 1.0602          | 0.7315 |
| 3.6398        | 0.7740 | 500  | 0.8942          | 0.6696 |
| 3.6398        | 0.9288 | 600  | 0.7116          | 0.5361 |
| 3.6398        | 1.0836 | 700  | 0.6648          | 0.5101 |
| 3.6398        | 1.2384 | 800  | 0.5869          | 0.4528 |
| 3.6398        | 1.3932 | 900  | 0.5698          | 0.4359 |
| 0.5976        | 1.5480 | 1000 | 0.5408          | 0.4112 |
| 0.5976        | 1.7028 | 1100 | 0.5229          | 0.4196 |
| 0.5976        | 1.8576 | 1200 | 0.5055          | 0.3955 |
| 0.5976        | 2.0124 | 1300 | 0.4808          | 0.3709 |
| 0.5976        | 2.1672 | 1400 | 0.4667          | 0.3580 |
| 0.443         | 2.3220 | 1500 | 0.4573          | 0.3582 |
| 0.443         | 2.4768 | 1600 | 0.4475          | 0.3452 |
| 0.443         | 2.6316 | 1700 | 0.4369          | 0.3478 |
| 0.443         | 2.7864 | 1800 | 0.4227          | 0.3298 |
| 0.443         | 2.9412 | 1900 | 0.4169          | 0.3271 |
| 0.3475        | 3.0960 | 2000 | 0.4200          | 0.3227 |


### Framework versions

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