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mms-1B_all_NCHLT_ZULU_5hr_v1

Automatic Speech Recognition
Transformers
Safetensors
Zulu
wav2vec2
Generated from Trainer
Eval Results
Inference Endpoints
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mms-1B_all_NCHLT_ZULU_5hr_v1 / README.md
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metadata
library_name: transformers
language:
  - zul
license: cc-by-nc-4.0
base_model: facebook/mms-1b-all
tags:
  - generated_from_trainer
datasets:
  - NCHLT_speech_corpus
metrics:
  - wer
model-index:
  - name: facebook mms-1b-all zulu - Beijuka Bruno
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: NCHLT_speech_corpus/Zulu
          type: NCHLT_speech_corpus
        metrics:
          - name: Wer
            type: wer
            value: 0.3831991599579979

facebook mms-1b-all zulu - Beijuka Bruno

This model is a fine-tuned version of facebook/mms-1b-all on the NCHLT_speech_corpus/Zulu dataset. It achieves the following results on the evaluation set:

  • Loss: 0.2668
  • Model Preparation Time: 0.0161
  • Wer: 0.3832
  • Cer: 0.0671

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: 4
  • eval_batch_size: 8
  • seed: 42
  • gradient_accumulation_steps: 8
  • total_train_batch_size: 32
  • optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 100
  • num_epochs: 100

Training results

Training Loss Epoch Step Validation Loss Model Preparation Time Wer Cer
75.5144 1.0 139 0.6716 0.0161 0.6021 0.1091
2.2356 2.0 278 0.1570 0.0161 0.2587 0.0378
1.6751 3.0 417 0.1414 0.0161 0.2355 0.0342
1.5484 4.0 556 0.1314 0.0161 0.2148 0.0308
1.4406 5.0 695 0.1275 0.0161 0.2100 0.0301
1.3547 6.0 834 0.1247 0.0161 0.1967 0.0288
1.3095 7.0 973 0.1191 0.0161 0.1909 0.0277
1.2359 8.0 1112 0.1176 0.0161 0.1865 0.0271
1.1879 9.0 1251 0.1173 0.0161 0.1818 0.0269
1.1513 10.0 1390 0.1181 0.0161 0.1818 0.0267
1.1037 11.0 1529 0.1145 0.0161 0.1797 0.0258
1.0629 12.0 1668 0.1090 0.0161 0.1726 0.0253
1.0302 13.0 1807 0.1087 0.0161 0.1705 0.0249
0.9804 14.0 1946 0.1059 0.0161 0.1654 0.0243
0.9649 15.0 2085 0.1098 0.0161 0.1644 0.0242
0.9074 16.0 2224 0.1052 0.0161 0.1624 0.0239
0.8947 17.0 2363 0.1045 0.0161 0.1579 0.0236
0.8442 18.0 2502 0.1063 0.0161 0.1572 0.0233
0.8151 19.0 2641 0.1036 0.0161 0.1566 0.0230
0.809 20.0 2780 0.1046 0.0161 0.1583 0.0234
0.8049 21.0 2919 0.1055 0.0161 0.1596 0.0229
0.7888 22.0 3058 0.1037 0.0161 0.1521 0.0221
0.7426 23.0 3197 0.1052 0.0161 0.1521 0.0223
0.7328 24.0 3336 0.1033 0.0161 0.1477 0.0221
0.7215 25.0 3475 0.1046 0.0161 0.1521 0.0224
0.6755 26.0 3614 0.1053 0.0161 0.1515 0.0225
0.6844 27.0 3753 0.1016 0.0161 0.1464 0.0217
0.6419 28.0 3892 0.1042 0.0161 0.1453 0.0214
0.6459 29.0 4031 0.1029 0.0161 0.1436 0.0209
0.6528 30.0 4170 0.1020 0.0161 0.1423 0.0214
0.6177 31.0 4309 0.1037 0.0161 0.1430 0.0213
0.5899 32.0 4448 0.1042 0.0161 0.1487 0.0225
0.6216 33.0 4587 0.1064 0.0161 0.1416 0.0212
0.5864 34.0 4726 0.1071 0.0161 0.1443 0.0217
0.5797 35.0 4865 0.1032 0.0161 0.1467 0.0215
0.5562 36.0 5004 0.1059 0.0161 0.1433 0.0213
0.5575 37.0 5143 0.1039 0.0161 0.1440 0.0214
0.5236 38.0 5282 0.1036 0.0161 0.1382 0.0207
0.5128 39.0 5421 0.1021 0.0161 0.1385 0.0203
0.4987 40.0 5560 0.1032 0.0161 0.1430 0.0208
0.5254 41.0 5699 0.1056 0.0161 0.1355 0.0204
0.5086 42.0 5838 0.1038 0.0161 0.1406 0.0206
0.4772 43.0 5977 0.1075 0.0161 0.1402 0.0205
0.4541 44.0 6116 0.1050 0.0161 0.1355 0.0200
0.4791 45.0 6255 0.1066 0.0161 0.1324 0.0198
0.4764 46.0 6394 0.1038 0.0161 0.1358 0.0198
0.4556 47.0 6533 0.1043 0.0161 0.1334 0.0197
0.4485 48.0 6672 0.1041 0.0161 0.1321 0.0195
0.44 49.0 6811 0.1071 0.0161 0.1385 0.0204
0.4265 50.0 6950 0.1086 0.0161 0.1361 0.0201
0.4388 51.0 7089 0.1066 0.0161 0.1304 0.0195
0.4326 52.0 7228 0.1087 0.0161 0.1331 0.0201
0.3916 53.0 7367 0.1091 0.0161 0.1368 0.0203
0.396 54.0 7506 0.1125 0.0161 0.1324 0.0198
0.4223 55.0 7645 0.1104 0.0161 0.1310 0.0195
0.3937 56.0 7784 0.1093 0.0161 0.1293 0.0193
0.4038 57.0 7923 0.1145 0.0161 0.1317 0.0197
0.402 58.0 8062 0.1112 0.0161 0.1331 0.0199
0.3912 59.0 8201 0.1109 0.0161 0.1270 0.0190
0.3888 60.0 8340 0.1103 0.0161 0.1249 0.0188
0.3797 61.0 8479 0.1074 0.0161 0.1276 0.0191
0.3682 62.0 8618 0.1111 0.0161 0.1293 0.0194
0.3678 63.0 8757 0.1117 0.0161 0.1304 0.0191
0.3611 64.0 8896 0.1136 0.0161 0.1253 0.0191
0.3406 65.0 9035 0.1114 0.0161 0.1232 0.0186
0.328 66.0 9174 0.1101 0.0161 0.1246 0.0187
0.3482 67.0 9313 0.1103 0.0161 0.1205 0.0182
0.344 68.0 9452 0.1130 0.0161 0.1215 0.0183
0.3465 69.0 9591 0.1115 0.0161 0.1290 0.0191
0.3411 70.0 9730 0.1124 0.0161 0.1249 0.0186
0.3182 71.0 9869 0.1142 0.0161 0.1225 0.0182
0.3303 72.0 10008 0.1116 0.0161 0.1232 0.0183
0.3632 73.0 10147 0.1099 0.0161 0.1229 0.0184
0.3183 74.0 10286 0.1128 0.0161 0.1266 0.0190
0.3215 75.0 10425 0.1119 0.0161 0.1229 0.0184
0.3019 76.0 10564 0.1132 0.0161 0.1253 0.0184
0.3275 77.0 10703 0.1103 0.0161 0.1212 0.0182

Framework versions

  • Transformers 4.47.1
  • Pytorch 2.1.0+cu118
  • Datasets 3.2.0
  • Tokenizers 0.21.0