---
library_name: transformers
license: apache-2.0
base_model: facebook/wav2vec2-large-xlsr-53
tags:
- generated_from_trainer
datasets:
- common_voice_13_0
metrics:
- wer
model-index:
- name: ierg4320_en_test
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: common_voice_13_0
      type: common_voice_13_0
      config: en
      split: None
      args: en
    metrics:
    - name: Wer
      type: wer
      value: 0.415272136474411
---

<!-- 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. -->

# ierg4320_en_test

This model is a fine-tuned version of [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on the common_voice_13_0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9548
- Wer: 0.4153

## 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: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 30
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step  | Validation Loss | Wer    |
|:-------------:|:-------:|:-----:|:---------------:|:------:|
| 5.0982        | 0.6211  | 400   | 2.9438          | 0.9938 |
| 1.7877        | 1.2422  | 800   | 1.0128          | 0.6645 |
| 0.8688        | 1.8634  | 1200  | 0.8012          | 0.5662 |
| 0.6808        | 2.4845  | 1600  | 0.8370          | 0.5366 |
| 0.6252        | 3.1056  | 2000  | 0.7710          | 0.5063 |
| 0.5532        | 3.7267  | 2400  | 0.7258          | 0.5041 |
| 0.5073        | 4.3478  | 2800  | 0.7337          | 0.4864 |
| 0.4834        | 4.9689  | 3200  | 0.7023          | 0.4777 |
| 0.4419        | 5.5901  | 3600  | 0.7542          | 0.4708 |
| 0.4326        | 6.2112  | 4000  | 0.7187          | 0.4647 |
| 0.4024        | 6.8323  | 4400  | 0.7212          | 0.4671 |
| 0.3809        | 7.4534  | 4800  | 0.7139          | 0.4582 |
| 0.3752        | 8.0745  | 5200  | 0.7296          | 0.4512 |
| 0.337         | 8.6957  | 5600  | 0.7207          | 0.4578 |
| 0.3305        | 9.3168  | 6000  | 0.7233          | 0.4528 |
| 0.3329        | 9.9379  | 6400  | 0.7178          | 0.4565 |
| 0.3047        | 10.5590 | 6800  | 0.7077          | 0.4518 |
| 0.2957        | 11.1801 | 7200  | 0.7788          | 0.4512 |
| 0.2913        | 11.8012 | 7600  | 0.7483          | 0.4528 |
| 0.2685        | 12.4224 | 8000  | 0.7644          | 0.4426 |
| 0.2666        | 13.0435 | 8400  | 0.7640          | 0.4427 |
| 0.2495        | 13.6646 | 8800  | 0.7959          | 0.4401 |
| 0.2501        | 14.2857 | 9200  | 0.7978          | 0.4494 |
| 0.2369        | 14.9068 | 9600  | 0.8217          | 0.4403 |
| 0.2282        | 15.5280 | 10000 | 0.8052          | 0.4359 |
| 0.2293        | 16.1491 | 10400 | 0.8688          | 0.4357 |
| 0.2165        | 16.7702 | 10800 | 0.8566          | 0.4385 |
| 0.2067        | 17.3913 | 11200 | 0.8504          | 0.4307 |
| 0.2034        | 18.0124 | 11600 | 0.8358          | 0.4346 |
| 0.1963        | 18.6335 | 12000 | 0.8729          | 0.4307 |
| 0.1846        | 19.2547 | 12400 | 0.8562          | 0.4349 |
| 0.189         | 19.8758 | 12800 | 0.8408          | 0.4266 |
| 0.1787        | 20.4969 | 13200 | 0.8424          | 0.4288 |
| 0.1757        | 21.1180 | 13600 | 0.8947          | 0.4327 |
| 0.1691        | 21.7391 | 14000 | 0.9070          | 0.4291 |
| 0.1652        | 22.3602 | 14400 | 0.8735          | 0.4299 |
| 0.1619        | 22.9814 | 14800 | 0.9224          | 0.4315 |
| 0.1544        | 23.6025 | 15200 | 0.9199          | 0.4278 |
| 0.1551        | 24.2236 | 15600 | 0.9089          | 0.4240 |
| 0.1449        | 24.8447 | 16000 | 0.9296          | 0.4229 |
| 0.1465        | 25.4658 | 16400 | 0.9476          | 0.4198 |
| 0.1434        | 26.0870 | 16800 | 0.9167          | 0.4193 |
| 0.1431        | 26.7081 | 17200 | 0.9492          | 0.4141 |
| 0.1335        | 27.3292 | 17600 | 0.9597          | 0.4185 |
| 0.1326        | 27.9503 | 18000 | 0.9516          | 0.4156 |
| 0.1333        | 28.5714 | 18400 | 0.9490          | 0.4153 |
| 0.1293        | 29.1925 | 18800 | 0.9605          | 0.4172 |
| 0.1257        | 29.8137 | 19200 | 0.9548          | 0.4153 |


### Framework versions

- Transformers 4.46.3
- Pytorch 2.5.1.post302
- Datasets 3.1.0
- Tokenizers 0.20.4