File size: 5,394 Bytes
f7d7396 d88a532 f7d7396 d88a532 f7d7396 f11c8aa f7d7396 90cb863 ead6749 9446cba f71c124 5090616 ffb9146 9d0706f 966c2bb 3c8a335 3e56a3b 089e757 f2af6d0 27d2cab 75e34c0 2a48291 5a1a33f 3cc0998 813da8f 6167d43 643560b d64ef4f 64eb224 d941abf 29c2054 ddd5ebe 145a531 cf08158 056e056 8294417 6065383 ef5a404 cb47401 877aa07 275f094 0c5557a 3ad27e8 bf108bd 0b1195d 3f91188 c38592b 157cd7d 2796f2e 48cf80c 1add3b9 9d5fbef ced8afa 803ae29 0e9002d c1f9b93 fd70364 e42c09b 8401040 17f253a 2a49800 6835d95 5ec88eb 7d98e8c e396708 f2a8c6d 75b5816 a61f7d9 aa83926 b90cf09 7d18ad3 393b684 731367c ba353a8 19f546d 470c766 57b43fd 94b3a61 ca5d308 6685563 d1948ee 4c91cb1 5b09a61 12a92ea 3370f2c 2e86d67 3366e08 fa679b4 4b52c4e b3169a2 04a3534 f1dda61 b6400f3 afe9343 b21a9e3 dfadcb9 65f6b4a 679ce88 e58cb47 cc7b47b 6d04691 2c769f6 f0944e3 8a23fd4 dace104 f11c8aa f7d7396 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 |
---
license: apache-2.0
base_model: mBart
tags:
- generated_from_keras_callback
model-index:
- name: bedus-creation/t5-small-dataset-ii-eng-lim
results: []
---
<!-- This model card has been generated automatically according to the information Keras had access to. You should
probably proofread and complete it, then remove this comment. -->
# bedus-creation/t5-small-dataset-ii-eng-lim
This model is a fine-tuned version of [mBart](https://huggingface.co/mBart) on an unknown dataset.
It achieves the following results on the evaluation set:
- Train Loss: 6.0880
- Validation Loss: 6.2594
- Epoch: 99
## 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 |
|:----------:|:---------------:|:-----:|
| 8.3860 | 7.8693 | 0 |
| 7.8568 | 7.6558 | 1 |
| 7.6900 | 7.5352 | 2 |
| 7.5904 | 7.4631 | 3 |
| 7.5155 | 7.4041 | 4 |
| 7.4554 | 7.3553 | 5 |
| 7.4005 | 7.3036 | 6 |
| 7.3547 | 7.2561 | 7 |
| 7.3104 | 7.2076 | 8 |
| 7.2651 | 7.1736 | 9 |
| 7.2302 | 7.1315 | 10 |
| 7.1888 | 7.0968 | 11 |
| 7.1616 | 7.0651 | 12 |
| 7.1290 | 7.0307 | 13 |
| 7.1066 | 7.0053 | 14 |
| 7.0729 | 6.9707 | 15 |
| 7.0388 | 6.9448 | 16 |
| 7.0169 | 6.9307 | 17 |
| 6.9924 | 6.9024 | 18 |
| 6.9716 | 6.8793 | 19 |
| 6.9503 | 6.8574 | 20 |
| 6.9252 | 6.8467 | 21 |
| 6.9136 | 6.8283 | 22 |
| 6.8915 | 6.8110 | 23 |
| 6.8697 | 6.7949 | 24 |
| 6.8531 | 6.7795 | 25 |
| 6.8336 | 6.7697 | 26 |
| 6.8255 | 6.7512 | 27 |
| 6.8080 | 6.7408 | 28 |
| 6.7928 | 6.7286 | 29 |
| 6.7752 | 6.7145 | 30 |
| 6.7629 | 6.7035 | 31 |
| 6.7467 | 6.6857 | 32 |
| 6.7329 | 6.6796 | 33 |
| 6.7216 | 6.6668 | 34 |
| 6.7067 | 6.6644 | 35 |
| 6.6935 | 6.6473 | 36 |
| 6.6810 | 6.6427 | 37 |
| 6.6713 | 6.6261 | 38 |
| 6.6551 | 6.6150 | 39 |
| 6.6422 | 6.6055 | 40 |
| 6.6346 | 6.5983 | 41 |
| 6.6254 | 6.5894 | 42 |
| 6.6066 | 6.5755 | 43 |
| 6.6023 | 6.5741 | 44 |
| 6.5900 | 6.5606 | 45 |
| 6.5781 | 6.5552 | 46 |
| 6.5597 | 6.5443 | 47 |
| 6.5578 | 6.5378 | 48 |
| 6.5426 | 6.5306 | 49 |
| 6.5304 | 6.5201 | 50 |
| 6.5179 | 6.5205 | 51 |
| 6.5142 | 6.5051 | 52 |
| 6.5010 | 6.4979 | 53 |
| 6.4840 | 6.5017 | 54 |
| 6.4787 | 6.4823 | 55 |
| 6.4734 | 6.4735 | 56 |
| 6.4619 | 6.4677 | 57 |
| 6.4496 | 6.4637 | 58 |
| 6.4344 | 6.4539 | 59 |
| 6.4290 | 6.4470 | 60 |
| 6.4159 | 6.4421 | 61 |
| 6.4069 | 6.4314 | 62 |
| 6.3964 | 6.4247 | 63 |
| 6.3887 | 6.4217 | 64 |
| 6.3783 | 6.4150 | 65 |
| 6.3670 | 6.4078 | 66 |
| 6.3593 | 6.3974 | 67 |
| 6.3500 | 6.3996 | 68 |
| 6.3359 | 6.3906 | 69 |
| 6.3358 | 6.3818 | 70 |
| 6.3298 | 6.3764 | 71 |
| 6.3158 | 6.3746 | 72 |
| 6.3026 | 6.3638 | 73 |
| 6.2904 | 6.3611 | 74 |
| 6.2861 | 6.3627 | 75 |
| 6.2820 | 6.3596 | 76 |
| 6.2658 | 6.3496 | 77 |
| 6.2554 | 6.3430 | 78 |
| 6.2552 | 6.3374 | 79 |
| 6.2468 | 6.3300 | 80 |
| 6.2316 | 6.3230 | 81 |
| 6.2314 | 6.3171 | 82 |
| 6.2198 | 6.3162 | 83 |
| 6.2084 | 6.3126 | 84 |
| 6.2020 | 6.3108 | 85 |
| 6.1906 | 6.3039 | 86 |
| 6.1851 | 6.2929 | 87 |
| 6.1749 | 6.2924 | 88 |
| 6.1678 | 6.3043 | 89 |
| 6.1576 | 6.2845 | 90 |
| 6.1566 | 6.2820 | 91 |
| 6.1454 | 6.2695 | 92 |
| 6.1351 | 6.2746 | 93 |
| 6.1313 | 6.2629 | 94 |
| 6.1211 | 6.2618 | 95 |
| 6.1107 | 6.2512 | 96 |
| 6.1092 | 6.2542 | 97 |
| 6.0974 | 6.2551 | 98 |
| 6.0880 | 6.2594 | 99 |
### Framework versions
- Transformers 4.33.2
- TensorFlow 2.13.0
- Datasets 2.14.5
- Tokenizers 0.13.3
|