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---
license: cc-by-nc-4.0
base_model: facebook/mms-1b-all
tags:
- generated_from_trainer
datasets:
- nena_speech_1_0_test
metrics:
- wer
model-index:
- name: wav2vec2-large-mms-1b-urmi-christian-nostress
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: nena_speech_1_0_test
type: nena_speech_1_0_test
config: urmi (christian)
split: test
args: urmi (christian)
metrics:
- name: Wer
type: wer
value: 0.944954128440367
---
<!-- 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-urmi-christian-nostress
This model is a fine-tuned version of [facebook/mms-1b-all](https://huggingface.co/facebook/mms-1b-all) on the nena_speech_1_0_test dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6617
- Wer: 0.9450
- Cer: 0.1846
## 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: 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: 100
- num_epochs: 5
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer | Cer |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|
| 14.5154 | 0.78 | 25 | 10.7711 | 1.0 | 0.9743 |
| 7.3688 | 1.56 | 50 | 6.3951 | 1.0 | 0.9408 |
| 3.895 | 2.34 | 75 | 2.4755 | 1.0 | 0.7579 |
| 1.6699 | 3.12 | 100 | 0.8689 | 0.9725 | 0.2286 |
| 1.1293 | 3.91 | 125 | 0.7194 | 0.9633 | 0.1981 |
| 0.9637 | 4.69 | 150 | 0.6617 | 0.9450 | 0.1846 |
### Framework versions
- Transformers 4.34.1
- Pytorch 2.1.0+cu121
- Datasets 2.14.6
- Tokenizers 0.14.1
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