transformers pytorch tensorboard wav2vec2 automatic-speech-recognition generated_from_trainer license:apache-2.0 endpoints_compatible region:us
---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: torgo_xlsr_finetune_M03_keep_all
  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. -->

# torgo_xlsr_finetune_M03_keep_all

This model is a fine-tuned version of [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.6155
- Wer: 0.2360

## 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: 0.0001
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 1000
- num_epochs: 20

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Wer    |
|:-------------:|:-----:|:-----:|:---------------:|:------:|
| 3.5946        | 0.56  | 1000  | 3.3418          | 1.0    |
| 2.3765        | 1.12  | 2000  | 1.8751          | 0.9367 |
| 1.0589        | 1.68  | 3000  | 1.4354          | 0.6588 |
| 0.7686        | 2.24  | 4000  | 1.3288          | 0.5193 |
| 0.7029        | 2.8   | 5000  | 1.2625          | 0.5071 |
| 0.5645        | 3.37  | 6000  | 1.3686          | 0.4331 |
| 0.5149        | 3.93  | 7000  | 1.2946          | 0.4392 |
| 0.4504        | 4.49  | 8000  | 1.4451          | 0.3793 |
| 0.4012        | 5.05  | 9000  | 1.3974          | 0.3324 |
| 0.3683        | 5.61  | 10000 | 1.6211          | 0.3553 |
| 0.3661        | 6.17  | 11000 | 1.4331          | 0.3488 |
| 0.3337        | 6.73  | 12000 | 1.6473          | 0.3454 |
| 0.3087        | 7.29  | 13000 | 1.4651          | 0.3096 |
| 0.2908        | 7.85  | 14000 | 1.3439          | 0.2844 |
| 0.2692        | 8.41  | 15000 | 1.2399          | 0.2871 |
| 0.262         | 8.97  | 16000 | 1.4219          | 0.3111 |
| 0.244         | 9.53  | 17000 | 1.5202          | 0.3065 |
| 0.2672        | 10.1  | 18000 | 1.3916          | 0.2840 |
| 0.2346        | 10.66 | 19000 | 1.6752          | 0.3077 |
| 0.2089        | 11.22 | 20000 | 1.4122          | 0.2734 |
| 0.2262        | 11.78 | 21000 | 1.4316          | 0.2795 |
| 0.2043        | 12.34 | 22000 | 1.6063          | 0.2943 |
| 0.1836        | 12.9  | 23000 | 1.5199          | 0.2726 |
| 0.1701        | 13.46 | 24000 | 1.6889          | 0.2722 |
| 0.1938        | 14.02 | 25000 | 1.5244          | 0.2619 |
| 0.1734        | 14.58 | 26000 | 1.8305          | 0.2692 |
| 0.1714        | 15.14 | 27000 | 1.6078          | 0.2539 |
| 0.1521        | 15.7  | 28000 | 1.8210          | 0.2665 |
| 0.1346        | 16.26 | 29000 | 1.7116          | 0.2653 |
| 0.1498        | 16.83 | 30000 | 1.4663          | 0.2432 |
| 0.1594        | 17.39 | 31000 | 1.5994          | 0.2402 |
| 0.1647        | 17.95 | 32000 | 1.5112          | 0.2356 |
| 0.1238        | 18.51 | 33000 | 1.6993          | 0.2429 |
| 0.1554        | 19.07 | 34000 | 1.5374          | 0.2379 |
| 0.1238        | 19.63 | 35000 | 1.6155          | 0.2360 |


### Framework versions

- Transformers 4.26.1
- Pytorch 2.2.0
- Datasets 2.16.1
- Tokenizers 0.13.3
