File size: 2,485 Bytes
eea89e7 c60ce76 a2f088d c60ce76 7b86932 a2f088d c60ce76 a2f088d 7b86932 a2f088d eea89e7 c60ce76 eea89e7 c60ce76 eea89e7 c60ce76 7b86932 eea89e7 c60ce76 eea89e7 c60ce76 eea89e7 c60ce76 eea89e7 c60ce76 eea89e7 c60ce76 eea89e7 c60ce76 eea89e7 c60ce76 eea89e7 c60ce76 eea89e7 c60ce76 eea89e7 c60ce76 eea89e7 c60ce76 7b86932 eea89e7 c60ce76 eea89e7 c60ce76 |
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 86 87 88 |
---
license: apache-2.0
tags:
- generated_from_trainer
base_model: facebook/wav2vec2-xls-r-300m
datasets:
- common_voice_13_0
metrics:
- wer
model-index:
- name: wav2vec2-xlsr-53-CV-demo-google-colab-Ezra_William_Prod17
results:
- task:
type: automatic-speech-recognition
name: Automatic Speech Recognition
dataset:
name: common_voice_13_0
type: common_voice_13_0
config: id
split: test
args: id
metrics:
- type: wer
value: 0.3124539085545723
name: Wer
---
<!-- 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-xlsr-53-CV-demo-google-colab-Ezra_William_Prod17
This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the common_voice_13_0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3690
- Wer: 0.3125
## 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: 0.0001
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 12
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 2.9121 | 1.0 | 278 | 2.8104 | 1.0 |
| 0.7904 | 2.0 | 556 | 0.5906 | 0.5911 |
| 0.4628 | 3.0 | 834 | 0.4488 | 0.5157 |
| 0.3279 | 4.0 | 1112 | 0.4175 | 0.4261 |
| 0.253 | 5.0 | 1390 | 0.3738 | 0.3929 |
| 0.1969 | 6.0 | 1668 | 0.3810 | 0.3847 |
| 0.1657 | 7.0 | 1946 | 0.3701 | 0.3587 |
| 0.1444 | 8.0 | 2224 | 0.3681 | 0.3457 |
| 0.1305 | 9.0 | 2502 | 0.3632 | 0.3229 |
| 0.1179 | 10.0 | 2780 | 0.3620 | 0.3225 |
| 0.1037 | 11.0 | 3058 | 0.3697 | 0.3136 |
| 0.0988 | 12.0 | 3336 | 0.3690 | 0.3125 |
### Framework versions
- Transformers 4.40.0
- Pytorch 2.2.2+cu121
- Datasets 2.19.0
- Tokenizers 0.19.1
|