File size: 2,213 Bytes
c74c71b a523242 c74c71b a523242 c74c71b a523242 c74c71b a523242 c74c71b a523242 c74c71b a523242 c74c71b a523242 c74c71b a523242 c74c71b a523242 c74c71b a523242 c74c71b a523242 c74c71b a523242 c74c71b a523242 c74c71b a523242 c74c71b a523242 c74c71b a523242 c74c71b a523242 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 |
---
license: apache-2.0
base_model: facebook/wav2vec2-large-xlsr-53
tags:
- generated_from_trainer
datasets:
- xtreme_s
metrics:
- wer
model-index:
- name: wav2vec2-XLS-R-Fleurs-demo-google-colab-Ezra_William_Prod5
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: xtreme_s
type: xtreme_s
config: fleurs.id_id
split: test
args: fleurs.id_id
metrics:
- name: Wer
type: wer
value: 0.5365963179164795
---
<!-- 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-XLS-R-Fleurs-demo-google-colab-Ezra_William_Prod5
This model is a fine-tuned version of [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on the xtreme_s dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9790
- Wer: 0.5366
## 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: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- 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: 600
- num_epochs: 60
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 4.9955 | 9.23 | 300 | 2.8534 | 1.0 |
| 1.7522 | 18.46 | 600 | 0.7939 | 0.7079 |
| 0.3374 | 27.69 | 900 | 0.8635 | 0.6423 |
| 0.1617 | 36.92 | 1200 | 0.9916 | 0.5929 |
| 0.1102 | 46.15 | 1500 | 0.9796 | 0.5648 |
| 0.0815 | 55.38 | 1800 | 0.9790 | 0.5366 |
### Framework versions
- Transformers 4.37.2
- Pytorch 2.2.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.1
|