---
library_name: transformers
license: apache-2.0
base_model: facebook/wav2vec2-base
tags:
- generated_from_trainer
datasets:
- common_voice_17_0
metrics:
- wer
model-index:
- name: wav2vec2-romanian-test
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: common_voice_17_0
      type: common_voice_17_0
      config: ro
      split: test
      args: ro
    metrics:
    - name: Wer
      type: wer
      value: 0.9989733059548255
---

<!-- 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-romanian-test

This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the common_voice_17_0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3928
- Wer: 0.9990

## 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: 32
- 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: 1000
- num_epochs: 30
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Wer    |
|:-------------:|:-------:|:----:|:---------------:|:------:|
| 4.4031        | 1.7730  | 500  | 1.7235          | 1.0    |
| 0.8308        | 3.5461  | 1000 | 0.5378          | 0.9997 |
| 0.4317        | 5.3191  | 1500 | 0.4410          | 0.9995 |
| 0.3127        | 7.0922  | 2000 | 0.4157          | 0.9992 |
| 0.2468        | 8.8652  | 2500 | 0.4119          | 0.9987 |
| 0.2086        | 10.6383 | 3000 | 0.3922          | 0.9995 |
| 0.1787        | 12.4113 | 3500 | 0.3861          | 0.9990 |
| 0.1601        | 14.1844 | 4000 | 0.3829          | 0.9987 |
| 0.1459        | 15.9574 | 4500 | 0.3929          | 0.9990 |
| 0.1315        | 17.7305 | 5000 | 0.3983          | 0.9990 |
| 0.1218        | 19.5035 | 5500 | 0.4068          | 0.9987 |
| 0.1138        | 21.2766 | 6000 | 0.4139          | 0.9990 |
| 0.107         | 23.0496 | 6500 | 0.3851          | 0.9990 |
| 0.0983        | 24.8227 | 7000 | 0.3820          | 0.9992 |
| 0.0937        | 26.5957 | 7500 | 0.3962          | 0.9990 |
| 0.0909        | 28.3688 | 8000 | 0.3928          | 0.9990 |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.4.1+cu124
- Datasets 2.21.0
- Tokenizers 0.19.1