| | --- |
| | language: |
| | - mt |
| | license: apache-2.0 |
| | tags: |
| | - automatic-speech-recognition |
| | - mozilla-foundation/common_voice_8_0 |
| | - generated_from_trainer |
| | - mt |
| | - robust-speech-event |
| | - model_for_talk |
| | - hf-asr-leaderboard |
| | datasets: |
| | - mozilla-foundation/common_voice_8_0 |
| | model-index: |
| | - name: wav2vec2-large-xls-r-1b-cv8-mt |
| | results: |
| | - task: |
| | name: Automatic Speech Recognition |
| | type: automatic-speech-recognition |
| | dataset: |
| | name: Common Voice 8 |
| | type: mozilla-foundation/common_voice_8_0 |
| | args: mt |
| | metrics: |
| | - name: Test WER |
| | type: wer |
| | value: 17.57 |
| | - name: Test CER |
| | type: cer |
| | value: 3.86 |
| | - task: |
| | name: Automatic Speech Recognition |
| | type: automatic-speech-recognition |
| | dataset: |
| | name: Robust Speech Event - Dev Data |
| | type: speech-recognition-community-v2/dev_data |
| | args: mt |
| | metrics: |
| | - name: Test WER |
| | type: wer |
| | value: null |
| | - name: Test CER |
| | type: cer |
| | value: null |
| | --- |
| | <!-- 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-1b-cv8-mt |
| |
|
| | This model is a fine-tuned version of [facebook/wav2vec2-xls-r-1b](https://huggingface.co/facebook/wav2vec2-xls-r-1b) on the common_voice dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 0.2210 |
| | - Wer: 0.1974 |
| | |
| | ## Model description |
| | |
| | Note: another version of this model is available with a KenLM 3gram model. This model performs better than this model. See https://huggingface.co/RuudVelo/wav2vec2-large-xls-r-1b-cv8-mt-lm |
| | |
| | ## Intended uses & limitations |
| | |
| | More information needed |
| | |
| | ## Training and evaluation data |
| | |
| | More information needed |
| | |
| | ## Training procedure |
| | |
| | ### Training hyperparameters |
| | |
| | The following config and hyperparameters were used during training: |
| | |
| | model = Wav2Vec2ForCTC.from_pretrained( |
| | "facebook/wav2vec2-xls-r-1b", |
| | attention_dropout=0.05, |
| | hidden_dropout=0.05, |
| | feat_proj_dropout=0.05, |
| | mask_time_prob=0.55, |
| | mask_feature_prob=0.10, |
| | layerdrop=0.05, |
| | ctc_zero_infinity=True, |
| | ctc_loss_reduction="mean", |
| | pad_token_id=processor.tokenizer.pad_token_id, |
| | vocab_size=len(processor.tokenizer), |
| | ) |
| | |
| | from transformers import TrainingArguments |
| |
|
| | training_args = TrainingArguments( |
| | output_dir=repo_name, |
| | group_by_length=True, |
| | per_device_train_batch_size=32, |
| | gradient_accumulation_steps=2, |
| | evaluation_strategy="steps", |
| | num_train_epochs=50, |
| | gradient_checkpointing=True, |
| | fp16=True, |
| | save_steps=400, |
| | eval_steps=400, |
| | logging_steps=400, |
| | learning_rate=5.5e-05, |
| | warmup_steps=500, |
| | save_total_limit=2, |
| | push_to_hub=True, |
| | report_to="tensorboard") |
| | |
| | ### Training results |
| | |
| | | Training Loss | Epoch | Step | Validation Loss | Wer | |
| | |:-------------:|:-----:|:----:|:---------------:|:------:| |
| | | 3.4564 | 13.33 | 400 | 0.3783 | 0.3981 | |
| | | 0.7931 | 26.66 | 800 | 0.2377 | 0.2298 | |
| | | 0.5364 | 39.98 | 1200 | 0.2210 | 0.1974 | |
| | |
| | Note that the test WER of 19.74 is different than the above reported 17.57. This was due to a bug which was found while processing files with an older version of the datasets library. The right library is listed below. |
| | |
| | ### Framework versions |
| | |
| | - Transformers 4.17.0.dev0 |
| | - Pytorch 1.10.2+cu102 |
| | - Datasets 1.18.3 |
| | - Tokenizers 0.11.0 |
| | |
