|
--- |
|
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 |
|
|
