---
license: apache-2.0
base_model: facebook/wav2vec2-large-xlsr-53
tags:
- automatic-speech-recognition
- DewiBrynJones/banc-trawsgrifiadau-bangor-normalized-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-NORMALIZED-WITH-CCV - DEFAULT dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4198
- Wer: 0.3249

## 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        | 0.1046 | 100  | 3.5059          | 1.0    |
| No log        | 0.2092 | 200  | 3.2687          | 1.0    |
| No log        | 0.3138 | 300  | 2.7369          | 1.0    |
| No log        | 0.4184 | 400  | 1.3039          | 0.8545 |
| 3.5426        | 0.5230 | 500  | 1.0518          | 0.7738 |
| 3.5426        | 0.6276 | 600  | 0.8396          | 0.6149 |
| 3.5426        | 0.7322 | 700  | 0.7548          | 0.5687 |
| 3.5426        | 0.8368 | 800  | 0.6869          | 0.5185 |
| 3.5426        | 0.9414 | 900  | 0.6501          | 0.4895 |
| 0.7785        | 1.0460 | 1000 | 0.5817          | 0.4501 |
| 0.7785        | 1.1506 | 1100 | 0.5647          | 0.4288 |
| 0.7785        | 1.2552 | 1200 | 0.5424          | 0.4279 |
| 0.7785        | 1.3598 | 1300 | 0.5264          | 0.4051 |
| 0.7785        | 1.4644 | 1400 | 0.5099          | 0.3977 |
| 0.5795        | 1.5690 | 1500 | 0.5058          | 0.3953 |
| 0.5795        | 1.6736 | 1600 | 0.4804          | 0.3789 |
| 0.5795        | 1.7782 | 1700 | 0.4672          | 0.3698 |
| 0.5795        | 1.8828 | 1800 | 0.4605          | 0.3712 |
| 0.5795        | 1.9874 | 1900 | 0.4491          | 0.3556 |
| 0.5057        | 2.0921 | 2000 | 0.4494          | 0.3453 |
| 0.5057        | 2.1967 | 2100 | 0.4432          | 0.3397 |
| 0.5057        | 2.3013 | 2200 | 0.4378          | 0.3351 |
| 0.5057        | 2.4059 | 2300 | 0.4291          | 0.3310 |
| 0.5057        | 2.5105 | 2400 | 0.4279          | 0.3294 |
| 0.3986        | 2.6151 | 2500 | 0.4234          | 0.3259 |
| 0.3986        | 2.7197 | 2600 | 0.4198          | 0.3249 |


### Framework versions

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