File size: 2,195 Bytes
564c5fb |
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 |
---
license: apache-2.0
base_model: ayertey01/wav2vec2-large-xlsr-53-AsanteTwi-06second
tags:
- generated_from_trainer
datasets:
- common_voice_13_0
metrics:
- wer
model-index:
- name: wav2vec2-large-xlsr-53-AsanteTwi-07
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: common_voice_13_0
type: common_voice_13_0
config: tw
split: test
args: tw
metrics:
- name: Wer
type: wer
value: 0.4375
---
<!-- 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-xlsr-53-AsanteTwi-07
This model is a fine-tuned version of [ayertey01/wav2vec2-large-xlsr-53-AsanteTwi-06second](https://huggingface.co/ayertey01/wav2vec2-large-xlsr-53-AsanteTwi-06second) on the common_voice_13_0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8573
- Wer: 0.4375
## 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
- 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: 200
- num_epochs: 100
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 0.0656 | 16.67 | 100 | 0.6553 | 0.5 |
| 0.0354 | 33.33 | 200 | 0.7952 | 0.5 |
| 0.0329 | 50.0 | 300 | 0.6705 | 0.4375 |
| 0.0261 | 66.67 | 400 | 0.7253 | 0.4375 |
| 0.0214 | 83.33 | 500 | 0.8056 | 0.4375 |
| 0.0236 | 100.0 | 600 | 0.8573 | 0.4375 |
### Framework versions
- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.0
- Tokenizers 0.13.3
|