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---
license: apache-2.0
base_model: pinot/wav2vec2-xls-r-300m-ja-cv-14_4
tags:
- generated_from_trainer
datasets:
- audiofolder
metrics:
- wer
model-index:
- name: cv-14-rakugo
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: audiofolder
type: audiofolder
config: default
split: train
args: default
metrics:
- name: Wer
type: wer
value: 0.6459627329192547
---
<!-- 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. -->
# cv-14-rakugo
This model is a fine-tuned version of [pinot/wav2vec2-xls-r-300m-ja-cv-14_4](https://huggingface.co/pinot/wav2vec2-xls-r-300m-ja-cv-14_4) on the audiofolder dataset.
It achieves the following results on the evaluation set:
- Loss: 5.1127
- Wer: 0.6460
## 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: 0.1
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 20
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| No log | 0.59 | 1 | 12.0211 | 0.3851 |
| No log | 1.78 | 3 | 12.0211 | 0.3851 |
| No log | 2.96 | 5 | 5.0175 | 0.4161 |
| No log | 3.56 | 6 | 2.7911 | 0.5093 |
| No log | 4.74 | 8 | 2.4989 | 0.5093 |
| No log | 5.93 | 10 | 4.0524 | 0.4907 |
| No log | 6.52 | 11 | 3.6691 | 0.4720 |
| No log | 7.7 | 13 | 4.6285 | 0.5280 |
| No log | 8.89 | 15 | 4.5016 | 0.5652 |
| No log | 9.48 | 16 | 4.4013 | 0.5776 |
| No log | 10.67 | 18 | 4.3718 | 0.6025 |
| No log | 11.85 | 20 | 5.1127 | 0.6460 |
### Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0
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