---
library_name: transformers
license: cc-by-nc-sa-4.0
base_model: fav-kky/wav2vec2-base-cs-80k-ClTRUS
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: wav2vec2-ctc
  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-ctc

This model is a fine-tuned version of [fav-kky/wav2vec2-base-cs-80k-ClTRUS](https://huggingface.co/fav-kky/wav2vec2-base-cs-80k-ClTRUS) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.5716
- Wer: 0.9831

## 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: 1e-05
- train_batch_size: 16
- eval_batch_size: 16
- 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_ratio: 0.3
- num_epochs: 60
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step  | Validation Loss | Wer    |
|:-------------:|:-------:|:-----:|:---------------:|:------:|
| 3.4027        | 2.1942  | 2000  | 3.5478          | 1.0    |
| 3.2864        | 4.3884  | 4000  | 3.4339          | 1.0    |
| 2.8505        | 6.5826  | 6000  | 2.8626          | 0.9998 |
| 2.5028        | 8.7767  | 8000  | 2.5475          | 0.9989 |
| 2.2853        | 10.9709 | 10000 | 2.3584          | 0.9989 |
| 2.1248        | 13.1651 | 12000 | 2.2147          | 0.9992 |
| 2.0013        | 15.3593 | 14000 | 2.1026          | 0.9989 |
| 1.8839        | 17.5535 | 16000 | 1.9910          | 0.9986 |
| 1.7885        | 19.7477 | 18000 | 1.9146          | 0.9991 |
| 1.7114        | 21.9419 | 20000 | 1.8460          | 0.9977 |
| 1.6532        | 24.1360 | 22000 | 1.7951          | 0.9968 |
| 1.606         | 26.3302 | 24000 | 1.7419          | 0.9959 |
| 1.5582        | 28.5244 | 26000 | 1.7155          | 0.9958 |
| 1.5257        | 30.7186 | 28000 | 1.6877          | 0.9917 |
| 1.4951        | 32.9128 | 30000 | 1.6671          | 0.9923 |
| 1.4748        | 35.1070 | 32000 | 1.6511          | 0.9902 |
| 1.4454        | 37.3012 | 34000 | 1.6320          | 0.9891 |
| 1.4241        | 39.4953 | 36000 | 1.6238          | 0.9884 |
| 1.4038        | 41.6895 | 38000 | 1.6056          | 0.9843 |
| 1.3902        | 43.8837 | 40000 | 1.5955          | 0.9839 |
| 1.3795        | 46.0779 | 42000 | 1.5908          | 0.9848 |
| 1.3708        | 48.2721 | 44000 | 1.5855          | 0.9833 |
| 1.3633        | 50.4663 | 46000 | 1.5863          | 0.9858 |
| 1.3564        | 52.6604 | 48000 | 1.5791          | 0.9830 |
| 1.3542        | 54.8546 | 50000 | 1.5714          | 0.9818 |
| 1.3379        | 57.0488 | 52000 | 1.5722          | 0.9824 |
| 1.3441        | 59.2430 | 54000 | 1.5716          | 0.9831 |


### Framework versions

- Transformers 4.45.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.20.0