Wav2vec2 Large Xls R 300m Dm32 Augmented | Sweet Tea Studio
Resources / Wav2vec2 Large Xls R 300m Dm32 Augmented 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
Verified source
Kind Other Base model facebook/wav2vec2-xls-r-300m Version v22af68bc33fbfaf3968910d4cb397af3edb5d4ba License apache-2.0 Publisher @SucharithaS C grade Model source
Kind Other
Base model facebook/wav2vec2-xls-r-300m
Version v22af68bc33fbfaf3968910d4cb397af3edb5d4ba
License apache-2.0
Parameters 300M
Tasks Video
Source Hugging Face --- 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: [] --- # 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
Sources & provenance
1 active source Source evidence
3 excerpts 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
license: apache-2.0 basemodel: facebook/wav2vec2-xls-r-300m tags: generatedfromtrainer metrics: accuracy f1 precision recall model-index: name: wav2vec2-large-xls-r-300m-dm32-augmented results: []
SucharithaS/wav2vec2-large-xls-r-300m-dm32-augmented
