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---
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
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