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---
license: cc-by-nc-4.0
base_model: facebook/mms-1b-all
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: mms_kas_speed1
results: []
---
<!-- 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. -->
# mms_kas_speed1
This model is a fine-tuned version of [facebook/mms-1b-all](https://huggingface.co/facebook/mms-1b-all) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8096
- Wer: 0.5141
## 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: 0.001
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- num_epochs: 30
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:-----:|:---------------:|:------:|
| 6.8005 | 0.12 | 100 | 1.8647 | 1.0536 |
| 1.8539 | 0.23 | 200 | 1.5445 | 0.9513 |
| 1.6826 | 0.35 | 300 | 1.5297 | 0.9316 |
| 1.6042 | 0.46 | 400 | 1.3865 | 0.9056 |
| 1.5353 | 0.58 | 500 | 1.3953 | 0.9043 |
| 1.5256 | 0.69 | 600 | 1.4043 | 0.9020 |
| 1.5491 | 0.81 | 700 | 1.3509 | 0.8694 |
| 1.475 | 0.93 | 800 | 1.4780 | 0.9107 |
| 1.4637 | 1.04 | 900 | 1.2694 | 0.8848 |
| 1.4401 | 1.16 | 1000 | 1.4087 | 0.8711 |
| 1.4125 | 1.27 | 1100 | 1.3147 | 0.8519 |
| 1.3864 | 1.39 | 1200 | 1.1807 | 0.8231 |
| 1.3294 | 1.5 | 1300 | 1.1504 | 0.8144 |
| 1.3606 | 1.62 | 1400 | 1.2630 | 0.8449 |
| 1.3254 | 1.74 | 1500 | 1.3070 | 0.8340 |
| 1.349 | 1.85 | 1600 | 1.1008 | 0.7980 |
| 1.3251 | 1.97 | 1700 | 1.1150 | 0.7854 |
| 1.3539 | 2.08 | 1800 | 1.0956 | 0.7943 |
| 1.266 | 2.2 | 1900 | 1.1196 | 0.7870 |
| 1.2787 | 2.31 | 2000 | 1.1659 | 0.7994 |
| 1.2902 | 2.43 | 2100 | 1.1099 | 0.7827 |
| 1.2761 | 2.55 | 2200 | 1.1361 | 0.8044 |
| 1.2559 | 2.66 | 2300 | 1.1497 | 0.8049 |
| 1.2294 | 2.78 | 2400 | 1.2398 | 0.8053 |
| 1.2438 | 2.89 | 2500 | 1.1234 | 0.7849 |
| 1.2736 | 3.01 | 2600 | 1.0433 | 0.7618 |
| 1.2337 | 3.12 | 2700 | 1.0905 | 0.7703 |
| 1.2079 | 3.24 | 2800 | 1.3420 | 0.8411 |
| 1.209 | 3.36 | 2900 | 1.0911 | 0.7879 |
| 1.2158 | 3.47 | 3000 | 1.2058 | 0.8023 |
| 1.176 | 3.59 | 3100 | 1.1623 | 0.7880 |
| 1.1775 | 3.7 | 3200 | 1.0644 | 0.7419 |
| 1.2212 | 3.82 | 3300 | 1.0549 | 0.7605 |
| 1.1774 | 3.94 | 3400 | 1.1500 | 0.7675 |
| 1.1046 | 4.05 | 3500 | 0.9748 | 0.7184 |
| 1.1979 | 4.17 | 3600 | 1.0100 | 0.7255 |
| 1.1544 | 4.28 | 3700 | 1.0290 | 0.7275 |
| 1.1558 | 4.4 | 3800 | 1.0180 | 0.7314 |
| 1.1593 | 4.51 | 3900 | 1.0051 | 0.7097 |
| 1.1415 | 4.63 | 4000 | 1.0115 | 0.7353 |
| 1.1399 | 4.75 | 4100 | 1.0527 | 0.7241 |
| 1.1297 | 4.86 | 4200 | 1.0546 | 0.7317 |
| 1.1137 | 4.98 | 4300 | 1.0818 | 0.7462 |
| 1.1948 | 5.09 | 4400 | 1.0758 | 0.7360 |
| 1.0913 | 5.21 | 4500 | 1.0204 | 0.7210 |
| 1.1632 | 5.32 | 4600 | 0.9644 | 0.7132 |
| 1.1216 | 5.44 | 4700 | 0.9569 | 0.6822 |
| 1.0728 | 5.56 | 4800 | 0.9980 | 0.7230 |
| 1.1097 | 5.67 | 4900 | 0.9867 | 0.7014 |
| 1.072 | 5.79 | 5000 | 0.9946 | 0.6972 |
| 1.1009 | 5.9 | 5100 | 0.9339 | 0.6818 |
| 1.1313 | 6.02 | 5200 | 0.9417 | 0.6842 |
| 1.0768 | 6.13 | 5300 | 0.9828 | 0.7195 |
| 1.0997 | 6.25 | 5400 | 1.0191 | 0.7258 |
| 1.0839 | 6.37 | 5500 | 1.0013 | 0.7045 |
| 1.0997 | 6.48 | 5600 | 0.9832 | 0.7159 |
| 1.0854 | 6.6 | 5700 | 1.0778 | 0.7397 |
| 1.0398 | 6.71 | 5800 | 1.0442 | 0.7268 |
| 1.0398 | 6.83 | 5900 | 1.0284 | 0.6932 |
| 1.0773 | 6.94 | 6000 | 1.1135 | 0.7522 |
| 1.0676 | 7.06 | 6100 | 0.9657 | 0.6816 |
| 1.0227 | 7.18 | 6200 | 0.9636 | 0.6695 |
| 1.0415 | 7.29 | 6300 | 0.9700 | 0.6709 |
| 1.0438 | 7.41 | 6400 | 0.9603 | 0.6662 |
| 1.0452 | 7.52 | 6500 | 0.9563 | 0.6674 |
| 1.0295 | 7.64 | 6600 | 0.9782 | 0.6633 |
| 1.0722 | 7.75 | 6700 | 0.9988 | 0.6752 |
| 0.9848 | 7.87 | 6800 | 0.9744 | 0.6897 |
| 1.0332 | 7.99 | 6900 | 0.9118 | 0.6485 |
| 1.0041 | 8.1 | 7000 | 0.8834 | 0.6329 |
| 1.0168 | 8.22 | 7100 | 0.9263 | 0.6365 |
| 1.0368 | 8.33 | 7200 | 1.0263 | 0.6867 |
| 1.0407 | 8.45 | 7300 | 1.0120 | 0.7029 |
| 1.0175 | 8.56 | 7400 | 0.8795 | 0.6295 |
| 1.0289 | 8.68 | 7500 | 0.8969 | 0.6294 |
| 1.018 | 8.8 | 7600 | 0.9635 | 0.6718 |
| 1.005 | 8.91 | 7700 | 0.9609 | 0.6625 |
| 1.0355 | 9.03 | 7800 | 0.8945 | 0.6302 |
| 0.9918 | 9.14 | 7900 | 0.8980 | 0.6427 |
| 1.0118 | 9.26 | 8000 | 0.8830 | 0.6211 |
| 1.0235 | 9.38 | 8100 | 0.8767 | 0.6207 |
| 0.9781 | 9.49 | 8200 | 0.8673 | 0.6104 |
| 0.9999 | 9.61 | 8300 | 0.9355 | 0.6280 |
| 0.9523 | 9.72 | 8400 | 0.8717 | 0.6121 |
| 0.9823 | 9.84 | 8500 | 0.8792 | 0.6220 |
| 1.0153 | 9.95 | 8600 | 0.9116 | 0.6311 |
| 1.0141 | 10.07 | 8700 | 0.8710 | 0.6157 |
| 0.9347 | 10.19 | 8800 | 0.9062 | 0.6315 |
| 0.9759 | 10.3 | 8900 | 0.8952 | 0.6227 |
| 0.9917 | 10.42 | 9000 | 0.8938 | 0.6283 |
| 0.9994 | 10.53 | 9100 | 0.8733 | 0.6225 |
| 0.9571 | 10.65 | 9200 | 0.9060 | 0.6364 |
| 0.9428 | 10.76 | 9300 | 0.8709 | 0.6237 |
| 0.9431 | 10.88 | 9400 | 0.8321 | 0.5943 |
| 0.8845 | 11.0 | 9500 | 0.8420 | 0.6032 |
| 0.9799 | 11.11 | 9600 | 0.8888 | 0.6028 |
| 0.977 | 11.23 | 9700 | 0.8922 | 0.6046 |
| 0.9392 | 11.34 | 9800 | 0.8611 | 0.5955 |
| 0.9547 | 11.46 | 9900 | 0.8472 | 0.5885 |
| 0.9546 | 11.57 | 10000 | 0.8656 | 0.5942 |
| 0.9166 | 11.69 | 10100 | 0.8665 | 0.5987 |
| 0.9515 | 11.81 | 10200 | 0.8541 | 0.6064 |
| 0.9418 | 11.92 | 10300 | 0.8384 | 0.5919 |
| 0.9039 | 12.04 | 10400 | 0.8492 | 0.5828 |
| 0.8965 | 12.15 | 10500 | 0.8454 | 0.5875 |
| 0.9085 | 12.27 | 10600 | 0.8676 | 0.6012 |
| 0.9113 | 12.38 | 10700 | 0.8536 | 0.5983 |
| 0.9243 | 12.5 | 10800 | 0.8816 | 0.5968 |
| 0.9469 | 12.62 | 10900 | 0.8526 | 0.5965 |
| 0.9149 | 12.73 | 11000 | 0.8378 | 0.5937 |
| 0.9198 | 12.85 | 11100 | 0.8462 | 0.5990 |
| 0.9557 | 12.96 | 11200 | 0.8405 | 0.5935 |
| 0.9775 | 13.08 | 11300 | 0.8657 | 0.5948 |
| 0.874 | 13.19 | 11400 | 0.8501 | 0.5864 |
| 0.9158 | 13.31 | 11500 | 0.8703 | 0.5879 |
| 0.8855 | 13.43 | 11600 | 0.8297 | 0.5895 |
| 0.9415 | 13.54 | 11700 | 0.8645 | 0.5887 |
| 0.8593 | 13.66 | 11800 | 0.8784 | 0.5928 |
| 0.9216 | 13.77 | 11900 | 0.8388 | 0.5816 |
| 0.9196 | 13.89 | 12000 | 0.8077 | 0.5743 |
| 0.9172 | 14.0 | 12100 | 0.8880 | 0.5897 |
| 0.9014 | 14.12 | 12200 | 0.8789 | 0.5974 |
| 0.8785 | 14.24 | 12300 | 0.8454 | 0.5726 |
| 0.8721 | 14.35 | 12400 | 0.8427 | 0.5672 |
| 0.8966 | 14.47 | 12500 | 0.8278 | 0.5709 |
| 0.8975 | 14.58 | 12600 | 0.8523 | 0.5813 |
| 0.8921 | 14.7 | 12700 | 0.8126 | 0.5697 |
| 0.8766 | 14.81 | 12800 | 0.8205 | 0.5665 |
| 0.8852 | 14.93 | 12900 | 0.8418 | 0.5640 |
| 0.8276 | 15.05 | 13000 | 0.8332 | 0.5785 |
| 0.851 | 15.16 | 13100 | 0.8144 | 0.5731 |
| 0.8916 | 15.28 | 13200 | 0.8452 | 0.5632 |
| 0.8623 | 15.39 | 13300 | 0.8398 | 0.5682 |
| 0.8932 | 15.51 | 13400 | 0.8249 | 0.5667 |
| 0.8442 | 15.62 | 13500 | 0.8300 | 0.5646 |
| 0.8592 | 15.74 | 13600 | 0.8153 | 0.5584 |
| 0.9012 | 15.86 | 13700 | 0.8109 | 0.5651 |
| 0.8537 | 15.97 | 13800 | 0.8101 | 0.5677 |
| 0.8812 | 16.09 | 13900 | 0.8057 | 0.5597 |
| 0.853 | 16.2 | 14000 | 0.8124 | 0.5645 |
| 0.8691 | 16.32 | 14100 | 0.8086 | 0.5621 |
| 0.844 | 16.44 | 14200 | 0.8074 | 0.5550 |
| 0.8612 | 16.55 | 14300 | 0.8361 | 0.5654 |
| 0.8315 | 16.67 | 14400 | 0.8216 | 0.5582 |
| 0.8665 | 16.78 | 14500 | 0.8307 | 0.5596 |
| 0.8487 | 16.9 | 14600 | 0.7991 | 0.5577 |
| 0.8567 | 17.01 | 14700 | 0.8181 | 0.5535 |
| 0.8288 | 17.13 | 14800 | 0.8308 | 0.5552 |
| 0.8199 | 17.25 | 14900 | 0.8383 | 0.5639 |
| 0.8264 | 17.36 | 15000 | 0.8355 | 0.5626 |
| 0.8374 | 17.48 | 15100 | 0.8925 | 0.5725 |
| 0.8549 | 17.59 | 15200 | 0.8190 | 0.5649 |
| 0.8164 | 17.71 | 15300 | 0.8422 | 0.5585 |
| 0.8575 | 17.82 | 15400 | 0.8195 | 0.5498 |
| 0.8553 | 17.94 | 15500 | 0.8355 | 0.5610 |
| 0.8234 | 18.06 | 15600 | 0.8214 | 0.5470 |
| 0.8293 | 18.17 | 15700 | 0.8215 | 0.5511 |
| 0.7996 | 18.29 | 15800 | 0.8075 | 0.5461 |
| 0.8468 | 18.4 | 15900 | 0.8182 | 0.5487 |
| 0.8138 | 18.52 | 16000 | 0.8309 | 0.5627 |
| 0.805 | 18.63 | 16100 | 0.8103 | 0.5575 |
| 0.8329 | 18.75 | 16200 | 0.8094 | 0.5402 |
| 0.8483 | 18.87 | 16300 | 0.8116 | 0.5428 |
| 0.8222 | 18.98 | 16400 | 0.8336 | 0.5413 |
| 0.8294 | 19.1 | 16500 | 0.8040 | 0.5419 |
| 0.8043 | 19.21 | 16600 | 0.7930 | 0.5427 |
| 0.8216 | 19.33 | 16700 | 0.8451 | 0.5574 |
| 0.7831 | 19.44 | 16800 | 0.8462 | 0.5546 |
| 0.8069 | 19.56 | 16900 | 0.8230 | 0.5481 |
| 0.8022 | 19.68 | 17000 | 0.7943 | 0.5441 |
| 0.8143 | 19.79 | 17100 | 0.8110 | 0.5406 |
| 0.8018 | 19.91 | 17200 | 0.8033 | 0.5366 |
| 0.7918 | 20.02 | 17300 | 0.8030 | 0.5344 |
| 0.8177 | 20.14 | 17400 | 0.8017 | 0.5377 |
| 0.7763 | 20.25 | 17500 | 0.8152 | 0.5411 |
| 0.8226 | 20.37 | 17600 | 0.8176 | 0.5403 |
| 0.7929 | 20.49 | 17700 | 0.8153 | 0.5406 |
| 0.7727 | 20.6 | 17800 | 0.8128 | 0.5378 |
| 0.8095 | 20.72 | 17900 | 0.8041 | 0.5493 |
| 0.7799 | 20.83 | 18000 | 0.8276 | 0.5411 |
| 0.8088 | 20.95 | 18100 | 0.8295 | 0.5426 |
| 0.7682 | 21.06 | 18200 | 0.8031 | 0.5349 |
| 0.7972 | 21.18 | 18300 | 0.8072 | 0.5269 |
| 0.7694 | 21.3 | 18400 | 0.8043 | 0.5270 |
| 0.7826 | 21.41 | 18500 | 0.8324 | 0.5343 |
| 0.7667 | 21.53 | 18600 | 0.8143 | 0.5316 |
| 0.7569 | 21.64 | 18700 | 0.8142 | 0.5347 |
| 0.7939 | 21.76 | 18800 | 0.8043 | 0.5338 |
| 0.7685 | 21.88 | 18900 | 0.8080 | 0.5408 |
| 0.7667 | 21.99 | 19000 | 0.8021 | 0.5308 |
| 0.7993 | 22.11 | 19100 | 0.8081 | 0.5393 |
| 0.7205 | 22.22 | 19200 | 0.8173 | 0.5408 |
| 0.7751 | 22.34 | 19300 | 0.8017 | 0.5267 |
| 0.7477 | 22.45 | 19400 | 0.8166 | 0.5382 |
| 0.7769 | 22.57 | 19500 | 0.8138 | 0.5341 |
| 0.7766 | 22.69 | 19600 | 0.8235 | 0.5349 |
| 0.7494 | 22.8 | 19700 | 0.8135 | 0.5304 |
| 0.8126 | 22.92 | 19800 | 0.8116 | 0.5317 |
| 0.7985 | 23.03 | 19900 | 0.8099 | 0.5303 |
| 0.7698 | 23.15 | 20000 | 0.8009 | 0.5323 |
| 0.7719 | 23.26 | 20100 | 0.8241 | 0.5411 |
| 0.7761 | 23.38 | 20200 | 0.8154 | 0.5289 |
| 0.7523 | 23.5 | 20300 | 0.7987 | 0.5285 |
| 0.7292 | 23.61 | 20400 | 0.7981 | 0.5255 |
| 0.7497 | 23.73 | 20500 | 0.8062 | 0.5180 |
| 0.7469 | 23.84 | 20600 | 0.7998 | 0.5287 |
| 0.7592 | 23.96 | 20700 | 0.8060 | 0.5265 |
| 0.7454 | 24.07 | 20800 | 0.8077 | 0.5296 |
| 0.7512 | 24.19 | 20900 | 0.8025 | 0.5277 |
| 0.7107 | 24.31 | 21000 | 0.8019 | 0.5284 |
| 0.7251 | 24.42 | 21100 | 0.7989 | 0.5248 |
| 0.7594 | 24.54 | 21200 | 0.8122 | 0.5249 |
| 0.7689 | 24.65 | 21300 | 0.8044 | 0.5225 |
| 0.7655 | 24.77 | 21400 | 0.8296 | 0.5247 |
| 0.7278 | 24.88 | 21500 | 0.8119 | 0.5245 |
| 0.7731 | 25.0 | 21600 | 0.7953 | 0.5222 |
| 0.7447 | 25.12 | 21700 | 0.8010 | 0.5208 |
| 0.7226 | 25.23 | 21800 | 0.8155 | 0.5212 |
| 0.7278 | 25.35 | 21900 | 0.8084 | 0.5229 |
| 0.7221 | 25.46 | 22000 | 0.8268 | 0.5277 |
| 0.739 | 25.58 | 22100 | 0.8054 | 0.5233 |
| 0.7657 | 25.69 | 22200 | 0.8004 | 0.5192 |
| 0.7624 | 25.81 | 22300 | 0.8081 | 0.5215 |
| 0.7264 | 25.93 | 22400 | 0.8069 | 0.5210 |
| 0.7596 | 26.04 | 22500 | 0.8084 | 0.5225 |
| 0.706 | 26.16 | 22600 | 0.8108 | 0.5195 |
| 0.7472 | 26.27 | 22700 | 0.8026 | 0.5159 |
| 0.7441 | 26.39 | 22800 | 0.8052 | 0.5158 |
| 0.7447 | 26.5 | 22900 | 0.8117 | 0.5185 |
| 0.6842 | 26.62 | 23000 | 0.7987 | 0.5139 |
| 0.7491 | 26.74 | 23100 | 0.7985 | 0.5140 |
| 0.7017 | 26.85 | 23200 | 0.8118 | 0.5158 |
| 0.7251 | 26.97 | 23300 | 0.8076 | 0.5172 |
| 0.7659 | 27.08 | 23400 | 0.8078 | 0.5160 |
| 0.7246 | 27.2 | 23500 | 0.8105 | 0.5159 |
| 0.7258 | 27.31 | 23600 | 0.8139 | 0.5183 |
| 0.7133 | 27.43 | 23700 | 0.8158 | 0.5150 |
| 0.6811 | 27.55 | 23800 | 0.8186 | 0.5145 |
| 0.7248 | 27.66 | 23900 | 0.7984 | 0.5108 |
| 0.7335 | 27.78 | 24000 | 0.8076 | 0.5162 |
| 0.6924 | 27.89 | 24100 | 0.8034 | 0.5129 |
| 0.7464 | 28.01 | 24200 | 0.8088 | 0.5131 |
| 0.7253 | 28.12 | 24300 | 0.8072 | 0.5119 |
| 0.7401 | 28.24 | 24400 | 0.8094 | 0.5125 |
| 0.7092 | 28.36 | 24500 | 0.8070 | 0.5153 |
| 0.7352 | 28.47 | 24600 | 0.8053 | 0.5128 |
| 0.7121 | 28.59 | 24700 | 0.8034 | 0.5139 |
| 0.6904 | 28.7 | 24800 | 0.8108 | 0.5136 |
| 0.7099 | 28.82 | 24900 | 0.8095 | 0.5141 |
| 0.6814 | 28.94 | 25000 | 0.8127 | 0.5167 |
| 0.6657 | 29.05 | 25100 | 0.8089 | 0.5139 |
| 0.721 | 29.17 | 25200 | 0.8117 | 0.5163 |
| 0.6886 | 29.28 | 25300 | 0.8120 | 0.5154 |
| 0.6974 | 29.4 | 25400 | 0.8087 | 0.5143 |
| 0.7067 | 29.51 | 25500 | 0.8102 | 0.5162 |
| 0.7311 | 29.63 | 25600 | 0.8119 | 0.5157 |
| 0.697 | 29.75 | 25700 | 0.8097 | 0.5145 |
| 0.7126 | 29.86 | 25800 | 0.8098 | 0.5139 |
| 0.7021 | 29.98 | 25900 | 0.8096 | 0.5141 |
### Framework versions
- Transformers 4.34.0.dev0
- Pytorch 2.1.0.dev20230523+cu117
- Datasets 2.14.5
- Tokenizers 0.13.2
|