File size: 1,771 Bytes
4d6ad0e bf19162 4d6ad0e bf19162 54df004 bf19162 4d6ad0e bf19162 4d6ad0e bf19162 4d6ad0e bf19162 4d6ad0e 54df004 bf19162 54df004 4d6ad0e 54df004 4d6ad0e |
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 |
---
library_name: transformers
license: apache-2.0
base_model: biodatlab/whisper-th-small-combined
tags:
- generated_from_trainer
model-index:
- name: outs
results: []
---
<!-- 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. -->
# outs
This model is a fine-tuned version of [biodatlab/whisper-th-small-combined](https://huggingface.co/biodatlab/whisper-th-small-combined) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1552
- Cer: 13.5275
## 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: 2e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 1000
- num_epochs: 10.0
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Cer |
|:-------------:|:------:|:----:|:---------------:|:-------:|
| 0.1733 | 1.8622 | 500 | 0.1206 | 7.2293 |
| 0.1159 | 3.7244 | 1000 | 0.1404 | 10.6943 |
| 0.0596 | 5.5866 | 1500 | 0.1665 | 12.2340 |
| 0.0399 | 7.4488 | 2000 | 0.1486 | 11.8316 |
| 0.0224 | 9.3110 | 2500 | 0.1552 | 13.5275 |
### Framework versions
- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.19.1
|