File size: 2,305 Bytes
ae9e5f6 8028334 d5874bb 8028334 f1a86ed d5874bb 8028334 d5874bb f1a86ed d5874bb ae9e5f6 8028334 ae9e5f6 8028334 ae9e5f6 f1a86ed 8028334 f1a86ed ae9e5f6 8028334 ae9e5f6 8028334 ae9e5f6 8028334 ae9e5f6 8028334 ae9e5f6 8028334 ae9e5f6 8028334 ae9e5f6 8028334 ae9e5f6 8028334 ae9e5f6 8028334 f1a86ed 8028334 ae9e5f6 8028334 ae9e5f6 8028334 f1a86ed ae9e5f6 8028334 ae9e5f6 8028334 |
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
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_Prod19
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: 0.34075405604719766
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_Prod19
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: 0.3575
- Wer: 0.3408
## 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: 9
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 2.9583 | 1.0 | 278 | 2.9214 | 1.0 |
| 2.8606 | 2.0 | 556 | 2.7724 | 1.0 |
| 1.1528 | 3.0 | 834 | 0.6902 | 0.6319 |
| 0.7003 | 4.0 | 1112 | 0.4844 | 0.4883 |
| 0.5853 | 5.0 | 1390 | 0.4030 | 0.4158 |
| 0.4685 | 6.0 | 1668 | 0.3945 | 0.3838 |
| 0.4273 | 7.0 | 1946 | 0.3824 | 0.3687 |
| 0.4116 | 8.0 | 2224 | 0.3643 | 0.3474 |
| 0.3858 | 9.0 | 2502 | 0.3575 | 0.3408 |
### Framework versions
- Transformers 4.40.1
- Pytorch 2.3.0+cu121
- Datasets 2.19.0
- Tokenizers 0.19.1
|