improved_4bars-mdl
This model is a fine-tuned version of JammyMachina/improved_4bars-mdl on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.8519
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: 5e-05
- train_batch_size: 21
- eval_batch_size: 24
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss |
---|---|---|---|
0.2574 | 0.1 | 1024 | 0.7889 |
0.2633 | 0.21 | 2048 | 0.7802 |
0.2635 | 0.31 | 3072 | 0.7877 |
0.2639 | 0.41 | 4096 | 0.7751 |
0.2625 | 0.52 | 5120 | 0.7836 |
0.2609 | 0.62 | 6144 | 0.7758 |
0.2597 | 0.73 | 7168 | 0.7923 |
0.2612 | 0.83 | 8192 | 0.8000 |
0.2612 | 0.93 | 9216 | 0.7935 |
0.2554 | 1.04 | 10240 | 0.7943 |
0.2524 | 1.14 | 11264 | 0.8015 |
0.2504 | 1.24 | 12288 | 0.7962 |
0.2524 | 1.35 | 13312 | 0.8086 |
0.2521 | 1.45 | 14336 | 0.8062 |
0.2503 | 1.55 | 15360 | 0.7998 |
0.2523 | 1.66 | 16384 | 0.8098 |
0.251 | 1.76 | 17408 | 0.8213 |
0.2509 | 1.86 | 18432 | 0.8138 |
0.2533 | 1.97 | 19456 | 0.8182 |
0.245 | 2.07 | 20480 | 0.8290 |
0.2432 | 2.18 | 21504 | 0.8328 |
0.2435 | 2.28 | 22528 | 0.8187 |
0.2423 | 2.38 | 23552 | 0.8238 |
0.2443 | 2.49 | 24576 | 0.8249 |
0.2431 | 2.59 | 25600 | 0.8253 |
0.2432 | 2.69 | 26624 | 0.8269 |
0.2421 | 2.8 | 27648 | 0.8282 |
0.2421 | 2.9 | 28672 | 0.8268 |
0.243 | 3.0 | 29696 | 0.8345 |
0.2367 | 3.11 | 30720 | 0.8424 |
0.237 | 3.21 | 31744 | 0.8374 |
0.2351 | 3.32 | 32768 | 0.8431 |
0.2374 | 3.42 | 33792 | 0.8425 |
0.2355 | 3.52 | 34816 | 0.8352 |
0.2373 | 3.63 | 35840 | 0.8452 |
0.2356 | 3.73 | 36864 | 0.8383 |
0.2343 | 3.83 | 37888 | 0.8444 |
0.2348 | 3.94 | 38912 | 0.8428 |
0.2349 | 4.04 | 39936 | 0.8480 |
0.2327 | 4.14 | 40960 | 0.8482 |
0.2337 | 4.25 | 41984 | 0.8510 |
0.2288 | 4.35 | 43008 | 0.8499 |
0.2299 | 4.45 | 44032 | 0.8522 |
0.2277 | 4.56 | 45056 | 0.8526 |
0.2301 | 4.66 | 46080 | 0.8518 |
0.2312 | 4.77 | 47104 | 0.8511 |
0.2284 | 4.87 | 48128 | 0.8507 |
0.2294 | 4.97 | 49152 | 0.8519 |
Framework versions
- Transformers 4.26.0.dev0
- Pytorch 1.13.1+cu116
- Datasets 2.7.1
- Tokenizers 0.13.2
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