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bedus-creation/eng-limbu-model-002
This model is a fine-tuned version of t5-small on an unknown dataset. It achieves the following results on the evaluation set:
- Train Loss: 6.3256
- Validation Loss: 6.8791
- Epoch: 149
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:
- optimizer: {'name': 'AdamWeightDecay', 'learning_rate': 2e-05, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False, 'weight_decay_rate': 0.01}
- training_precision: float32
Training results
| Train Loss | Validation Loss | Epoch |
|---|---|---|
| 9.1271 | 8.7408 | 0 |
| 8.7900 | 8.5152 | 1 |
| 8.5937 | 8.2894 | 2 |
| 8.3940 | 8.1041 | 3 |
| 8.2510 | 7.9661 | 4 |
| 8.1174 | 7.8669 | 5 |
| 8.0494 | 7.7932 | 6 |
| 7.9458 | 7.7451 | 7 |
| 7.9505 | 7.7095 | 8 |
| 7.8572 | 7.6815 | 9 |
| 7.8339 | 7.6505 | 10 |
| 7.7734 | 7.6216 | 11 |
| 7.7619 | 7.5968 | 12 |
| 7.6829 | 7.5746 | 13 |
| 7.6692 | 7.5552 | 14 |
| 7.6492 | 7.5385 | 15 |
| 7.6289 | 7.5218 | 16 |
| 7.6122 | 7.5045 | 17 |
| 7.5815 | 7.4880 | 18 |
| 7.5513 | 7.4715 | 19 |
| 7.5763 | 7.4553 | 20 |
| 7.5594 | 7.4393 | 21 |
| 7.5081 | 7.4242 | 22 |
| 7.5002 | 7.4095 | 23 |
| 7.4710 | 7.3945 | 24 |
| 7.4328 | 7.3806 | 25 |
| 7.4605 | 7.3668 | 26 |
| 7.4181 | 7.3531 | 27 |
| 7.4068 | 7.3394 | 28 |
| 7.3782 | 7.3256 | 29 |
| 7.3866 | 7.3126 | 30 |
| 7.3759 | 7.2999 | 31 |
| 7.3582 | 7.2871 | 32 |
| 7.3298 | 7.2749 | 33 |
| 7.3253 | 7.2629 | 34 |
| 7.3116 | 7.2507 | 35 |
| 7.2920 | 7.2392 | 36 |
| 7.2491 | 7.2281 | 37 |
| 7.2856 | 7.2164 | 38 |
| 7.2565 | 7.2051 | 39 |
| 7.2665 | 7.1948 | 40 |
| 7.2424 | 7.1845 | 41 |
| 7.2314 | 7.1761 | 42 |
| 7.2365 | 7.1665 | 43 |
| 7.2141 | 7.1573 | 44 |
| 7.1938 | 7.1478 | 45 |
| 7.1938 | 7.1406 | 46 |
| 7.1646 | 7.1310 | 47 |
| 7.1463 | 7.1211 | 48 |
| 7.1652 | 7.1138 | 49 |
| 7.1247 | 7.1046 | 50 |
| 7.1294 | 7.0959 | 51 |
| 7.1428 | 7.0880 | 52 |
| 7.1101 | 7.0802 | 53 |
| 7.1195 | 7.0716 | 54 |
| 7.1366 | 7.0651 | 55 |
| 7.0781 | 7.0582 | 56 |
| 7.0638 | 7.0514 | 57 |
| 7.0636 | 7.0451 | 58 |
| 7.0585 | 7.0417 | 59 |
| 7.0634 | 7.0361 | 60 |
| 7.0355 | 7.0308 | 61 |
| 7.0535 | 7.0254 | 62 |
| 7.0424 | 7.0164 | 63 |
| 7.0075 | 7.0088 | 64 |
| 6.9984 | 7.0014 | 65 |
| 7.0072 | 6.9999 | 66 |
| 6.9888 | 6.9955 | 67 |
| 6.9763 | 6.9886 | 68 |
| 6.9629 | 6.9813 | 69 |
| 6.9639 | 6.9783 | 70 |
| 6.9769 | 6.9769 | 71 |
| 6.9634 | 6.9742 | 72 |
| 6.9616 | 6.9649 | 73 |
| 6.9513 | 6.9576 | 74 |
| 6.9337 | 6.9532 | 75 |
| 6.9313 | 6.9530 | 76 |
| 6.9044 | 6.9489 | 77 |
| 6.9203 | 6.9422 | 78 |
| 6.8990 | 6.9383 | 79 |
| 6.8745 | 6.9327 | 80 |
| 6.8947 | 6.9276 | 81 |
| 6.8696 | 6.9231 | 82 |
| 6.8699 | 6.9164 | 83 |
| 6.8697 | 6.9124 | 84 |
| 6.8504 | 6.9148 | 85 |
| 6.8526 | 6.9150 | 86 |
| 6.8367 | 6.9149 | 87 |
| 6.8351 | 6.9062 | 88 |
| 6.8641 | 6.8909 | 89 |
| 6.8182 | 6.8856 | 90 |
| 6.8246 | 6.8864 | 91 |
| 6.8376 | 6.8883 | 92 |
| 6.8005 | 6.8863 | 93 |
| 6.7832 | 6.8796 | 94 |
| 6.7806 | 6.8772 | 95 |
| 6.7876 | 6.8747 | 96 |
| 6.7757 | 6.8751 | 97 |
| 6.7548 | 6.8719 | 98 |
| 6.7685 | 6.8615 | 99 |
| 6.7535 | 6.8581 | 100 |
| 6.7244 | 6.8610 | 101 |
| 6.7281 | 6.8611 | 102 |
| 6.7342 | 6.8570 | 103 |
| 6.7141 | 6.8576 | 104 |
| 6.6942 | 6.8612 | 105 |
| 6.6985 | 6.8586 | 106 |
| 6.6644 | 6.8645 | 107 |
| 6.6835 | 6.8587 | 108 |
| 6.6289 | 6.8558 | 109 |
| 6.6531 | 6.8526 | 110 |
| 6.6052 | 6.8572 | 111 |
| 6.6341 | 6.8709 | 112 |
| 6.6392 | 6.8692 | 113 |
| 6.6320 | 6.8524 | 114 |
| 6.6142 | 6.8514 | 115 |
| 6.6246 | 6.8451 | 116 |
| 6.6171 | 6.8430 | 117 |
| 6.5912 | 6.8589 | 118 |
| 6.5726 | 6.8688 | 119 |
| 6.5736 | 6.8585 | 120 |
| 6.5748 | 6.8444 | 121 |
| 6.5666 | 6.8534 | 122 |
| 6.5968 | 6.8574 | 123 |
| 6.5416 | 6.8524 | 124 |
| 6.5257 | 6.8571 | 125 |
| 6.5724 | 6.8563 | 126 |
| 6.5125 | 6.8564 | 127 |
| 6.5113 | 6.8526 | 128 |
| 6.4686 | 6.8539 | 129 |
| 6.5103 | 6.8597 | 130 |
| 6.4730 | 6.8658 | 131 |
| 6.4959 | 6.8621 | 132 |
| 6.4437 | 6.8786 | 133 |
| 6.4526 | 6.8719 | 134 |
| 6.4328 | 6.8596 | 135 |
| 6.4678 | 6.8595 | 136 |
| 6.4271 | 6.8595 | 137 |
| 6.4482 | 6.8579 | 138 |
| 6.3347 | 6.8731 | 139 |
| 6.4074 | 6.8643 | 140 |
| 6.4132 | 6.8596 | 141 |
| 6.3897 | 6.8648 | 142 |
| 6.3232 | 6.8800 | 143 |
| 6.3461 | 6.8751 | 144 |
| 6.3384 | 6.8623 | 145 |
| 6.3414 | 6.8728 | 146 |
| 6.3258 | 6.9066 | 147 |
| 6.3153 | 6.8956 | 148 |
| 6.3256 | 6.8791 | 149 |
Framework versions
- Transformers 4.32.1
- TensorFlow 2.12.0
- Datasets 2.14.4
- Tokenizers 0.13.3
