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---
license: cc-by-nc-4.0
base_model: facebook/mms-1b-all
tags:
- generated_from_trainer
datasets:
- audiofolder
metrics:
- wer
model-index:
- name: wav2vec2-large-mms-1b-even-pakendorf
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: 0.7591335595927331
---
<!-- 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-large-mms-1b-even-pakendorf
This model is a fine-tuned version of [facebook/mms-1b-all](https://huggingface.co/facebook/mms-1b-all) on the audiofolder dataset.
It achieves the following results on the evaluation set:
- Loss: inf
- Wer: 0.7591
- Cer: 0.2779
## 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: 0.001
- train_batch_size: 4
- 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: 100
- num_epochs: 4
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer | Cer |
|:-------------:|:------:|:----:|:---------------:|:------:|:------:|
| 1.847 | 0.1895 | 300 | inf | 0.9027 | 0.3662 |
| 1.8253 | 0.3790 | 600 | inf | 0.9087 | 0.3658 |
| 1.6956 | 0.5685 | 900 | inf | 0.8723 | 0.3412 |
| 1.6616 | 0.7581 | 1200 | inf | 0.8437 | 0.3209 |
| 1.5962 | 0.9476 | 1500 | inf | 0.8392 | 0.3217 |
| 1.6299 | 1.1371 | 1800 | inf | 0.8447 | 0.3201 |
| 1.5242 | 1.3266 | 2100 | inf | 0.8191 | 0.3076 |
| 1.582 | 1.5161 | 2400 | inf | 0.8157 | 0.3070 |
| 1.5555 | 1.7056 | 2700 | inf | 0.8092 | 0.3061 |
| 1.5476 | 1.8951 | 3000 | inf | 0.7999 | 0.3009 |
| 1.4725 | 2.0846 | 3300 | inf | 0.7945 | 0.2952 |
| 1.4902 | 2.2742 | 3600 | inf | 0.7834 | 0.2936 |
| 1.3984 | 2.4637 | 3900 | inf | 0.7836 | 0.2900 |
| 1.4633 | 2.6532 | 4200 | inf | 0.7942 | 0.2872 |
| 1.4533 | 2.8427 | 4500 | inf | 0.7804 | 0.2863 |
| 1.4814 | 3.0322 | 4800 | inf | 0.7728 | 0.2859 |
| 1.4397 | 3.2217 | 5100 | inf | 0.7693 | 0.2818 |
| 1.4218 | 3.4112 | 5400 | inf | 0.7702 | 0.2831 |
| 1.3655 | 3.6008 | 5700 | inf | 0.7650 | 0.2795 |
| 1.34 | 3.7903 | 6000 | inf | 0.7615 | 0.2792 |
| 1.3351 | 3.9798 | 6300 | inf | 0.7591 | 0.2779 |
### Framework versions
- Transformers 4.42.0.dev0
- Pytorch 2.3.1+cu121
- Datasets 2.19.2
- Tokenizers 0.19.1
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