xlsr-finetuned / README.md
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---
base_model: classla/wav2vec2-xls-r-parlaspeech-hr
tags:
- generated_from_trainer
datasets:
- audiofolder
metrics:
- wer
model-index:
- name: xlsr-finetuned
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: audiofolder
type: audiofolder
config: default
split: test
args: default
metrics:
- name: Wer
type: wer
value: 1.0
---
<!-- 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. -->
# xlsr-finetuned
This model is a fine-tuned version of [classla/wav2vec2-xls-r-parlaspeech-hr](https://huggingface.co./classla/wav2vec2-xls-r-parlaspeech-hr) on the audiofolder dataset.
It achieves the following results on the evaluation set:
- Loss: 2.1218
- Wer: 1.0
## 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: 4
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 1
- training_steps: 4
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:----:|:---------------:|:----:|
| No log | 1.0 | 1 | 14.0503 | 20.0 |
| 3.5057 | 2.0 | 2 | 5.3734 | 4.0 |
| 3.5057 | 3.0 | 3 | 2.8914 | 1.0 |
| 1.0014 | 4.0 | 4 | 2.1218 | 1.0 |
### Framework versions
- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3