File size: 6,843 Bytes
6b13995 |
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 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 |
---
library_name: transformers
license: mit
base_model: openai/whisper-large-v3-turbo
tags:
- generated_from_trainer
datasets:
- fleurs
metrics:
- wer
model-index:
- name: whisper-large-v3-turbo-greek-greece
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: fleurs
type: fleurs
config: el_gr
split: None
args: el_gr
metrics:
- name: Wer
type: wer
value: 11.059118170434324
---
<!-- 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. -->
# whisper-large-v3-turbo-greek-greece
This model is a fine-tuned version of [openai/whisper-large-v3-turbo](https://huggingface.co/openai/whisper-large-v3-turbo) on the fleurs dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3006
- Model Preparation Time: 0.0067
- Wer Ortho: 26.8701
- Wer: 11.0591
## 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: 1e-05
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 128
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.06
- num_epochs: 1
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Model Preparation Time | Wer Ortho | Wer |
|:-------------:|:------:|:----:|:---------------:|:----------------------:|:---------:|:-------:|
| 0.6129 | 0.0204 | 32 | 0.2996 | 0.0067 | 29.5644 | 14.1172 |
| 0.5021 | 0.0408 | 64 | 0.3064 | 0.0067 | 29.0414 | 14.0381 |
| 0.5068 | 0.0612 | 96 | 0.3116 | 0.0067 | 29.3261 | 14.2226 |
| 0.5049 | 0.0816 | 128 | 0.3000 | 0.0067 | 28.5317 | 13.8404 |
| 0.5289 | 0.1020 | 160 | 0.3261 | 0.0067 | 29.5048 | 14.3413 |
| 0.4464 | 0.1224 | 192 | 0.3336 | 0.0067 | 29.5115 | 14.2292 |
| 0.4324 | 0.1428 | 224 | 0.3267 | 0.0067 | 28.9157 | 13.8865 |
| 0.4376 | 0.1632 | 256 | 0.3319 | 0.0067 | 29.8292 | 14.7367 |
| 0.4623 | 0.1836 | 288 | 0.3493 | 0.0067 | 29.5379 | 14.2424 |
| 0.4494 | 0.2040 | 320 | 0.3210 | 0.0067 | 28.9620 | 13.7415 |
| 0.4541 | 0.2244 | 352 | 0.3284 | 0.0067 | 29.0348 | 13.7349 |
| 0.4262 | 0.2448 | 384 | 0.3169 | 0.0067 | 28.7369 | 13.2077 |
| 0.4365 | 0.2652 | 416 | 0.3131 | 0.0067 | 28.7369 | 13.1484 |
| 0.4701 | 0.2856 | 448 | 0.3144 | 0.0067 | 28.5118 | 13.0759 |
| 0.4256 | 0.3060 | 480 | 0.3017 | 0.0067 | 28.4126 | 13.2868 |
| 0.4437 | 0.3264 | 512 | 0.3080 | 0.0067 | 28.6111 | 13.3724 |
| 0.4147 | 0.3468 | 544 | 0.3141 | 0.0067 | 28.1875 | 12.4629 |
| 0.4089 | 0.3672 | 576 | 0.3150 | 0.0067 | 28.2669 | 12.9638 |
| 0.4448 | 0.3876 | 608 | 0.3221 | 0.0067 | 28.5979 | 12.8913 |
| 0.4354 | 0.4080 | 640 | 0.3091 | 0.0067 | 28.1875 | 12.7859 |
| 0.3877 | 0.4284 | 672 | 0.3174 | 0.0067 | 28.0816 | 12.5816 |
| 0.4411 | 0.4488 | 704 | 0.3130 | 0.0067 | 28.4788 | 13.0693 |
| 0.4056 | 0.4692 | 736 | 0.3168 | 0.0067 | 28.3000 | 12.4366 |
| 0.4043 | 0.4896 | 768 | 0.3291 | 0.0067 | 28.1213 | 12.4695 |
| 0.4265 | 0.5100 | 800 | 0.3230 | 0.0067 | 27.8565 | 12.0082 |
| 0.4075 | 0.5304 | 832 | 0.3062 | 0.0067 | 27.4990 | 12.1400 |
| 0.4075 | 0.5508 | 864 | 0.3137 | 0.0067 | 27.6711 | 12.0675 |
| 0.4312 | 0.5712 | 896 | 0.3086 | 0.0067 | 27.6777 | 11.8302 |
| 0.4294 | 0.5916 | 928 | 0.3034 | 0.0067 | 27.4262 | 12.1202 |
| 0.4268 | 0.6120 | 960 | 0.3126 | 0.0067 | 27.9558 | 12.3707 |
| 0.4385 | 0.6325 | 992 | 0.3156 | 0.0067 | 28.0087 | 12.3113 |
| 0.3886 | 0.6529 | 1024 | 0.3043 | 0.0067 | 27.6115 | 11.8566 |
| 0.3761 | 0.6733 | 1056 | 0.3076 | 0.0067 | 27.2541 | 11.8434 |
| 0.4109 | 0.6937 | 1088 | 0.3125 | 0.0067 | 27.4924 | 12.0214 |
| 0.4231 | 0.7141 | 1120 | 0.3025 | 0.0067 | 27.3070 | 11.8368 |
| 0.4126 | 0.7345 | 1152 | 0.3058 | 0.0067 | 27.3070 | 11.7577 |
| 0.3999 | 0.7549 | 1184 | 0.3056 | 0.0067 | 26.9694 | 11.4677 |
| 0.4354 | 0.7753 | 1216 | 0.3031 | 0.0067 | 27.4725 | 11.6589 |
| 0.4036 | 0.7957 | 1248 | 0.2979 | 0.0067 | 27.2210 | 11.4611 |
| 0.3972 | 0.8161 | 1280 | 0.3043 | 0.0067 | 27.3467 | 11.4348 |
| 0.3478 | 0.8365 | 1312 | 0.3055 | 0.0067 | 27.4063 | 11.5139 |
| 0.3915 | 0.8569 | 1344 | 0.3015 | 0.0067 | 27.1813 | 11.4743 |
| 0.4092 | 0.8773 | 1376 | 0.2999 | 0.0067 | 27.0356 | 11.3952 |
| 0.4042 | 0.8977 | 1408 | 0.2974 | 0.0067 | 27.0025 | 11.3227 |
| 0.4332 | 0.9181 | 1440 | 0.3026 | 0.0067 | 27.2739 | 11.4282 |
| 0.4164 | 0.9385 | 1472 | 0.2996 | 0.0067 | 27.0158 | 11.1777 |
| 0.3774 | 0.9589 | 1504 | 0.3009 | 0.0067 | 27.0820 | 11.0987 |
| 0.3934 | 0.9793 | 1536 | 0.3006 | 0.0067 | 26.8701 | 11.0591 |
| 0.3695 | 0.9997 | 1568 | 0.3020 | 0.0067 | 26.9032 | 11.0921 |
### Framework versions
- Transformers 4.51.3
- Pytorch 2.5.1
- Datasets 3.6.0
- Tokenizers 0.21.1
|