Wav2vec2 Large Xls R 300m Dm32 Augmented
This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on an unknown dataset. It achieves the following results on the evaluation set: Loss: 0.6039 Accuracy: 0.7083 F1: 0.6901 Precision: 0.7176 Recall: 0.7083
Modellquelle
- Art
- Other
- Dateigröße
- 1,18 GB
- Basismodell
- facebook/wav2vec2-xls-r-300m
- Version
- vRevision 22af68b
- Aktualisiert
- 2. Okt. 2026
- Verleger
- @SucharithaS
- Downloads
- 6
- Parameter
- 300M
- Aufgaben
- Video zu Video
- Quelle
- Hugging Face
Quellenbeschreibung
wav2vec2-large-xls-r-300m-dm32-augmented
This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.6039
- Accuracy: 0.7083
- F1: 0.6901
- Precision: 0.7176
- Recall: 0.7083
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: 3e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 200
- num_epochs: 25
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
|---|---|---|---|---|---|---|---|
| No log | 2.39 | 34 | 0.6977 | 0.4583 | 0.4274 | 0.5139 | 0.4583 |
| No log | 4.77 | 68 | 0.6900 | 0.5833 | 0.4298 | 0.3403 | 0.5833 |
| 0.6925 | 7.16 | 102 | 0.6795 | 0.5833 | 0.4298 | 0.3403 | 0.5833 |
| 0.6925 | 9.54 | 136 | 0.6839 | 0.5833 | 0.4298 | 0.3403 | 0.5833 |
| 0.6925 | 11.93 | 170 | 0.6921 | 0.625 | 0.625 | 0.625 | 0.625 |
| 0.6902 | 14.32 | 204 | 0.6799 | 0.6042 | 0.4752 | 0.7642 | 0.6042 |
| 0.6902 | 16.7 | 238 | 0.6752 | 0.5833 | 0.4298 | 0.3403 | 0.5833 |
| 0.6902 | 19.09 | 272 | 0.6352 | 0.7083 | 0.7083 | 0.7083 | 0.7083 |
| 0.6717 | 21.47 | 306 | 0.6492 | 0.7083 | 0.6901 | 0.7176 | 0.7083 |
| 0.6717 | 23.86 | 340 | 0.6039 | 0.7083 | 0.6901 | 0.7176 | 0.7083 |
Framework versions
- Transformers 4.37.2
- Pytorch 2.10.0+cu128
- Datasets 4.0.0
- Tokenizers 0.15.2
Quellen
1 Quelle
Quellen
1 QuelleVerifiziert 2. Okt.
Modellartefakte
1 Artefakt
Modellartefakte
1 ArtefaktQuellenauszüge
3 Auszüge
Quellenauszüge
3 Auszüge--- license: apache-2.0 base_model: facebook/wav2vec2-xls-r-300m tags: - generated_from_trainer metrics: - accuracy - f1 - precision - recall model-index: - name: wav2vec2-large-xls-r-300m-dm32-augmented 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. --> # wav2vec2-large-xls-r-300m-dm32-augmented This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 0.6039 - Accuracy: 0.7083 - F1: 0.6901 - Precision: 0.7176 - Recall: 0.7083 ## 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: 3e-05 - train_batch_size: 4 - eval_batch_size: 4 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 16 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - lr_scheduler_warmup_steps: 200 - num_epochs: 25 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall | |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:| | No log | 2.39 | 34 | 0.6977 | 0.4583 | 0.4274 | 0.5139 | 0.4583 | | No log | 4.77 | 68 | 0.6900 | 0.5833 | 0.4298 | 0.3403 | 0.5833 | | 0.6925 | 7.16 | 102 | 0.6795 | 0.5833 | 0.4298 | 0.3403 | 0.5833 | | 0.6925 | 9.54 | 136 | 0.6839 | 0.5833 | 0.4298 | 0.3403 | 0.5833 | | 0.6925 | 11.93 | 170 | 0.6921 | 0.625 | 0.625 | 0.625 | 0.625 | | 0.6902 | 14.32 | 204 | 0.6799 | 0.6042 | 0.4752 | 0.7642 | 0.6042 | | 0.6902 | 16.7 | 238 | 0.6752 | 0.5833 | 0.4298 | 0.3403 | 0.5833 | | 0.6902 | 19.09 | 272 | 0.6352 | 0.7083 | 0.7083 | 0.7083 | 0.7083 | | 0.6717 | 21.47 | 306 | 0.6492 | 0.7083 | 0.6901 | 0.7176 | 0.7083 | | 0.6717 | 23.86 | 340 | 0.6039 | 0.7083 | 0.6901 | 0.7176 | 0.7083 | ### Framework versions - Transformers 4.37.2 - Pytorch 2.10.0+cu128 - Datasets 4.0.0 - Tokenizers 0.15.2
Source context: 6 downloads · 0 likes · Repo SucharithaS/wav2vec2-large-xls-r-300m-dm32-augmented
Source context: 2 downloads · 0 likes · Repo SucharithaS/wav2vec2-large-xls-r-300m-dm32-augmented
