Update README.md

README.md

@@ -3,77 +3,28 @@ license: apache-2.0
 base_model: facebook/wav2vec2-large-xlsr-53
 tags:
 - automatic-speech-recognition
-- ./data-configs/btb-cv.json
 - generated_from_trainer
 metrics:
 - wer
 model-index:
 - name: wav2vec2-xlsr-53-ft-btb-cv-cy-cand
   results: []
+datasets:
+- techiaith/commonvoice_18_0_cy
+- techiaith/banc-trawsgrifiadau-bangor
+language:
+- cy
+pipeline_tag: automatic-speech-recognition
 ---
 
-<!-- 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-xlsr-53-ft-btb-cv-cy
 
-# wav2vec2-xlsr-53-ft-btb-cv-cy-cand
+This model is a version of [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) 
+fine-tuned on Welsh language read-speech from [commonvoice_18_cy](https://huggingface.co/datasets/techiaith/commonvoice_18_0_cy) 
+and spontaneous speech from [Bangor Transcriptions 24.10](https://huggingface.co/datasets/techiaith/banc-trawsgrifiadau-bangor/tree/24.10)
 
-This model is a fine-tuned version of [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on an unknown dataset.
-It achieves the following results on the evaluation set:
-- Loss: inf
-- Wer: 0.3598
+It achieves the following WER results on the Bangor Transcriptions test set:
 
-## 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: 0.0003
-- train_batch_size: 8
-- eval_batch_size: 64
-- seed: 42
-- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
-- lr_scheduler_type: linear
-- lr_scheduler_warmup_steps: 800
-- training_steps: 8000
-- mixed_precision_training: Native AMP
-
-### Training results
-
-| Training Loss | Epoch  | Step | Validation Loss | Wer    |
-|:-------------:|:------:|:----:|:---------------:|:------:|
-| 4.6973        | 0.0714 | 500  | inf             | 1.0    |
-| 1.448         | 0.1428 | 1000 | inf             | 0.7574 |
-| 1.053         | 0.2142 | 1500 | inf             | 0.6584 |
-| 0.9304        | 0.2856 | 2000 | inf             | 0.5963 |
-| 0.8755        | 0.3569 | 2500 | inf             | 0.5946 |
-| 0.8238        | 0.4283 | 3000 | inf             | 0.5392 |
-| 0.7819        | 0.4997 | 3500 | inf             | 0.4967 |
-| 0.729         | 0.5711 | 4000 | inf             | 0.4834 |
-| 0.6923        | 0.6425 | 4500 | inf             | 0.4564 |
-| 0.7052        | 0.7139 | 5000 | inf             | 0.4346 |
-| 0.6675        | 0.7853 | 5500 | inf             | 0.4163 |
-| 0.6217        | 0.8567 | 6000 | inf             | 0.3962 |
-| 0.5954        | 0.9280 | 6500 | inf             | 0.3883 |
-| 0.5687        | 0.9994 | 7000 | inf             | 0.3746 |
-| 0.477         | 1.0708 | 7500 | inf             | 0.3647 |
-| 0.4804        | 1.1422 | 8000 | inf             | 0.3598 |
-
-
-### Framework versions
-
-- Transformers 4.44.0
-- Pytorch 2.4.0+cu121
-- Datasets 2.21.0
-- Tokenizers 0.19.1
+- WER: 36.23
+- CER: 12.55
+