README.md

metadata

language:
  - sv-SE
license: apache-2.0
tags:
  - automatic-speech-recognition
  - mozilla-foundation/common_voice_8_0
  - generated_from_trainer
  - sv
  - robust-speech-event
  - hf-asr-leaderboard
datasets:
  - mozilla-foundation/common_voice_8_0
model-index:
  - name: XLS-R-300M - Swedish - CV8 - v2
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: Common Voice 8
          type: mozilla-foundation/common_voice_8_0
          args: sv-SE
        metrics:
          - name: Test WER
            type: wer
            value: 17.33
          - name: Test CER
            type: cer
            value: 5.8
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: Robust Speech Event - Dev Data
          type: speech-recognition-community-v2/dev_data
          args: sv
        metrics:
          - name: Test WER
            type: wer
            value: 27.01
          - name: Test CER
            type: cer
            value: 12.92

This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the MOZILLA-FOUNDATION/COMMON_VOICE_8_0 - SV-SE dataset. It achieves the following results on the evaluation set:

• Loss: 0.2779
• Wer: 0.2525

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: 7.5e-05
• train_batch_size: 8
• eval_batch_size: 8
• seed: 42
• gradient_accumulation_steps: 4
• total_train_batch_size: 32
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• lr_scheduler_warmup_steps: 2000
• num_epochs: 50.0
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
3.3224	1.37	500	3.3354	1.0
2.9318	2.74	1000	2.9361	1.0000
2.1371	4.11	1500	1.1157	0.8359
1.6883	5.48	2000	0.6003	0.6314
1.5812	6.85	2500	0.4746	0.4725
1.5145	8.22	3000	0.4376	0.4736
1.4763	9.59	3500	0.4006	0.3863
1.4215	10.96	4000	0.3783	0.3629
1.3638	12.33	4500	0.3555	0.3425
1.3561	13.7	5000	0.3340	0.3228
1.3406	15.07	5500	0.3373	0.3295
1.3055	16.44	6000	0.3432	0.3210
1.3048	17.81	6500	0.3282	0.3118
1.2863	19.18	7000	0.3226	0.3018
1.2389	20.55	7500	0.3050	0.2986
1.2361	21.92	8000	0.3048	0.2980
1.2263	23.29	8500	0.3011	0.2977
1.2225	24.66	9000	0.3017	0.2959
1.2044	26.03	9500	0.2977	0.2782
1.2017	27.4	10000	0.2966	0.2781
1.1912	28.77	10500	0.2999	0.2786
1.1658	30.14	11000	0.2991	0.2757
1.148	31.51	11500	0.2915	0.2684
1.1423	32.88	12000	0.2913	0.2643
1.123	34.25	12500	0.2777	0.2630
1.1297	35.62	13000	0.2873	0.2646
1.0987	36.98	13500	0.2829	0.2619
1.0873	38.36	14000	0.2864	0.2608
1.0848	39.73	14500	0.2827	0.2577
1.0628	41.1	15000	0.2896	0.2581
1.0815	42.47	15500	0.2814	0.2561
1.0587	43.83	16000	0.2738	0.2542
1.0709	45.21	16500	0.2785	0.2578
1.0512	46.57	17000	0.2793	0.2539
1.0396	47.94	17500	0.2788	0.2525
1.0481	49.31	18000	0.2777	0.2534

Evaluation Commands

1. To evaluate on mozilla-foundation/common_voice_7_0 with split test

python eval.py --model_id patrickvonplaten/xls-r-300m-sv-cv8 --dataset mozilla-foundation/common_voice_8_0 --config sv-SE --split test

2. To evaluate on speech-recognition-community-v2/dev_data

python eval.py --model_id patrickvonplaten/xls-r-300m-sv-cv8 --dataset speech-recognition-community-v2/dev_data --config sv --split validation --chunk_length_s 5.0 --stride_length_s 1.0

Framework versions

• Transformers 4.17.0.dev0
• Pytorch 1.10.1+cu113
• Datasets 1.18.4.dev0
• Tokenizers 0.10.3