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libri-alpha-0.75-Temp-1-attention-3-layers-distil-with-6-layers
This model is a fine-tuned version of on the None dataset. It achieves the following results on the evaluation set:
- Loss: 176.0337
- Wer: 0.4211
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: 2e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.2
- num_epochs: 30
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Wer |
---|---|---|---|---|
818.3828 | 0.19 | 100 | 299.9131 | 0.6582 |
836.7686 | 0.37 | 200 | 297.5387 | 0.6554 |
787.5465 | 0.56 | 300 | 294.7996 | 0.6512 |
804.7234 | 0.75 | 400 | 292.2293 | 0.6463 |
812.2401 | 0.93 | 500 | 289.8000 | 0.6398 |
796.3071 | 1.12 | 600 | 287.0509 | 0.6351 |
755.1163 | 1.31 | 700 | 283.9792 | 0.6282 |
789.9813 | 1.49 | 800 | 280.8894 | 0.6241 |
746.3034 | 1.68 | 900 | 278.0494 | 0.6193 |
762.4461 | 1.87 | 1000 | 276.0318 | 0.6131 |
750.3801 | 2.06 | 1100 | 273.0303 | 0.6117 |
759.8897 | 2.24 | 1200 | 270.4828 | 0.6072 |
766.8752 | 2.43 | 1300 | 267.3370 | 0.6017 |
747.1767 | 2.62 | 1400 | 264.8568 | 0.5978 |
709.7859 | 2.8 | 1500 | 262.1042 | 0.5940 |
682.8446 | 2.99 | 1600 | 258.8314 | 0.5878 |
678.7934 | 3.18 | 1700 | 255.1844 | 0.5842 |
688.9065 | 3.36 | 1800 | 253.7106 | 0.5789 |
676.8735 | 3.55 | 1900 | 252.6307 | 0.5784 |
671.5541 | 3.74 | 2000 | 249.2319 | 0.5723 |
661.5926 | 3.92 | 2100 | 247.3242 | 0.5669 |
669.4624 | 4.11 | 2200 | 243.3662 | 0.5623 |
643.5416 | 4.3 | 2300 | 241.4045 | 0.5609 |
663.1716 | 4.49 | 2400 | 239.8308 | 0.5571 |
645.2939 | 4.67 | 2500 | 236.4551 | 0.5498 |
643.487 | 4.86 | 2600 | 234.4706 | 0.5463 |
661.5359 | 5.05 | 2700 | 233.3655 | 0.5420 |
620.0827 | 5.23 | 2800 | 230.9604 | 0.5410 |
623.4608 | 5.42 | 2900 | 229.2104 | 0.5346 |
614.5616 | 5.61 | 3000 | 227.1311 | 0.5315 |
610.5325 | 5.79 | 3100 | 224.7402 | 0.5308 |
609.3737 | 5.98 | 3200 | 224.0515 | 0.5268 |
577.5857 | 6.17 | 3300 | 222.1016 | 0.5211 |
600.8658 | 6.35 | 3400 | 220.7187 | 0.5190 |
579.8273 | 6.54 | 3500 | 219.0504 | 0.5167 |
577.1318 | 6.73 | 3600 | 216.5892 | 0.5138 |
598.4185 | 6.92 | 3700 | 214.8921 | 0.5092 |
574.2131 | 7.1 | 3800 | 214.3345 | 0.5069 |
558.845 | 7.29 | 3900 | 212.7756 | 0.5027 |
562.5259 | 7.48 | 4000 | 210.9550 | 0.5001 |
542.4756 | 7.66 | 4100 | 210.1631 | 0.4984 |
531.1471 | 7.85 | 4200 | 208.7503 | 0.4963 |
578.4951 | 8.04 | 4300 | 206.8714 | 0.4942 |
549.3659 | 8.22 | 4400 | 206.2005 | 0.4905 |
549.3715 | 8.41 | 4500 | 204.9378 | 0.4897 |
526.3116 | 8.6 | 4600 | 204.2942 | 0.4877 |
556.9892 | 8.78 | 4700 | 203.8197 | 0.4838 |
536.3161 | 8.97 | 4800 | 201.7986 | 0.4811 |
566.8901 | 9.16 | 4900 | 201.8660 | 0.4819 |
527.6058 | 9.35 | 5000 | 201.0037 | 0.4783 |
537.7548 | 9.53 | 5100 | 199.5784 | 0.4765 |
521.8008 | 9.72 | 5200 | 199.2429 | 0.4740 |
527.2388 | 9.91 | 5300 | 199.3108 | 0.4754 |
510.5078 | 10.09 | 5400 | 198.8395 | 0.4722 |
543.6402 | 10.28 | 5500 | 198.2866 | 0.4706 |
534.623 | 10.47 | 5600 | 197.0690 | 0.4686 |
504.127 | 10.65 | 5700 | 198.0624 | 0.4706 |
522.8051 | 10.84 | 5800 | 196.0252 | 0.4649 |
543.651 | 11.03 | 5900 | 193.4206 | 0.4655 |
515.7955 | 11.21 | 6000 | 193.9807 | 0.4640 |
504.2811 | 11.4 | 6100 | 193.1624 | 0.4613 |
506.7597 | 11.59 | 6200 | 193.1175 | 0.4607 |
496.2182 | 11.77 | 6300 | 191.9746 | 0.4607 |
524.1124 | 11.96 | 6400 | 192.0139 | 0.4571 |
502.1757 | 12.15 | 6500 | 191.7406 | 0.4561 |
517.2375 | 12.34 | 6600 | 190.3192 | 0.4552 |
507.2228 | 12.52 | 6700 | 189.7269 | 0.4559 |
495.0334 | 12.71 | 6800 | 189.9307 | 0.4541 |
487.9488 | 12.9 | 6900 | 187.9196 | 0.4506 |
481.8289 | 13.08 | 7000 | 188.2804 | 0.4495 |
497.7955 | 13.27 | 7100 | 188.5640 | 0.4495 |
495.9639 | 13.46 | 7200 | 188.2054 | 0.4482 |
477.9561 | 13.64 | 7300 | 187.2503 | 0.4490 |
489.6057 | 13.83 | 7400 | 186.3044 | 0.4460 |
486.4094 | 14.02 | 7500 | 185.7658 | 0.4444 |
490.18 | 14.21 | 7600 | 185.7803 | 0.4463 |
481.2339 | 14.39 | 7700 | 185.2366 | 0.4456 |
497.7487 | 14.58 | 7800 | 184.6401 | 0.4416 |
492.7409 | 14.77 | 7900 | 184.4930 | 0.4424 |
480.0516 | 14.95 | 8000 | 184.3564 | 0.4426 |
503.3515 | 15.14 | 8100 | 184.0443 | 0.4397 |
483.1878 | 15.33 | 8200 | 183.3429 | 0.4382 |
468.6728 | 15.51 | 8300 | 183.1123 | 0.4366 |
473.9079 | 15.7 | 8400 | 182.9552 | 0.4385 |
471.2554 | 15.89 | 8500 | 181.8883 | 0.4370 |
482.9162 | 16.07 | 8600 | 181.9493 | 0.4383 |
473.6775 | 16.26 | 8700 | 182.3769 | 0.4374 |
490.9736 | 16.45 | 8800 | 181.8944 | 0.4357 |
473.9841 | 16.63 | 8900 | 181.1866 | 0.4343 |
458.6111 | 16.82 | 9000 | 180.9161 | 0.4327 |
473.312 | 17.01 | 9100 | 180.8257 | 0.4328 |
474.3633 | 17.2 | 9200 | 180.2251 | 0.4310 |
466.0219 | 17.38 | 9300 | 180.4953 | 0.4328 |
456.4883 | 17.57 | 9400 | 180.3950 | 0.4321 |
473.9428 | 17.76 | 9500 | 180.0498 | 0.4297 |
467.2524 | 17.94 | 9600 | 179.7389 | 0.4317 |
453.7509 | 18.13 | 9700 | 179.1797 | 0.4283 |
480.6095 | 18.32 | 9800 | 178.6612 | 0.4292 |
476.2359 | 18.5 | 9900 | 178.4738 | 0.4277 |
468.8798 | 18.69 | 10000 | 178.2498 | 0.4277 |
469.7198 | 18.88 | 10100 | 178.3403 | 0.4268 |
456.8305 | 19.07 | 10200 | 177.9058 | 0.4258 |
459.8746 | 19.25 | 10300 | 177.8065 | 0.4256 |
461.4241 | 19.44 | 10400 | 177.2613 | 0.4244 |
463.9236 | 19.63 | 10500 | 177.2336 | 0.4267 |
432.5434 | 19.81 | 10600 | 177.2254 | 0.4262 |
440.5167 | 20.0 | 10700 | 177.1022 | 0.4242 |
455.6524 | 20.19 | 10800 | 177.0475 | 0.4243 |
463.6909 | 20.37 | 10900 | 176.5024 | 0.4229 |
460.1803 | 20.56 | 11000 | 176.3350 | 0.4198 |
459.226 | 20.75 | 11100 | 176.1349 | 0.4204 |
453.7939 | 20.93 | 11200 | 175.5934 | 0.4213 |
452.2502 | 21.12 | 11300 | 175.7082 | 0.4221 |
469.455 | 21.31 | 11400 | 175.9399 | 0.4222 |
460.2929 | 21.49 | 11500 | 176.0337 | 0.4211 |
Framework versions
- Transformers 4.23.1
- Pytorch 1.12.1
- Datasets 2.6.1
- Tokenizers 0.13.1