File size: 2,721 Bytes
e6f04f1 |
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 89 90 91 92 93 94 |
---
license: apache-2.0
base_model: facebook/wav2vec2-large-xlsr-53
tags:
- generated_from_trainer
datasets:
- common_voice
metrics:
- wer
model-index:
- name: wav2vec2-common_voice-tr-demo
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: common_voice
type: common_voice
config: tr
split: test
args: tr
metrics:
- name: Wer
type: wer
value: 0.3489939740578082
---
<!-- 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-common_voice-tr-demo
This model is a fine-tuned version of [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on the common_voice dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3802
- Wer: 0.3490
## 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: 0.0003
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 15.0
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| No log | 0.92 | 100 | 3.5826 | 1.0 |
| No log | 1.83 | 200 | 3.0218 | 0.9999 |
| No log | 2.75 | 300 | 0.8985 | 0.8036 |
| No log | 3.67 | 400 | 0.5992 | 0.6197 |
| 3.1629 | 4.59 | 500 | 0.4968 | 0.5340 |
| 3.1629 | 5.5 | 600 | 0.4646 | 0.5045 |
| 3.1629 | 6.42 | 700 | 0.4316 | 0.4425 |
| 3.1629 | 7.34 | 800 | 0.4500 | 0.4735 |
| 3.1629 | 8.26 | 900 | 0.4114 | 0.4123 |
| 0.2226 | 9.17 | 1000 | 0.4162 | 0.4019 |
| 0.2226 | 10.09 | 1100 | 0.3999 | 0.3824 |
| 0.2226 | 11.01 | 1200 | 0.4048 | 0.3842 |
| 0.2226 | 11.93 | 1300 | 0.3789 | 0.3602 |
| 0.2226 | 12.84 | 1400 | 0.4024 | 0.3536 |
| 0.1015 | 13.76 | 1500 | 0.3899 | 0.3575 |
| 0.1015 | 14.68 | 1600 | 0.3802 | 0.3490 |
### Framework versions
- Transformers 4.32.0.dev0
- Pytorch 2.0.1+cu118
- Datasets 2.14.0
- Tokenizers 0.13.3
|