genz_model1 / README.md
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---
license: apache-2.0
base_model: t5-small
tags:
- generated_from_trainer
metrics:
- bleu
model-index:
- name: genz_model1
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. -->
# genz_model1
This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.2337
- Bleu: 37.5629
- Gen Len: 15.215
## 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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 50
### Training results
| Training Loss | Epoch | Step | Validation Loss | Bleu | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|
| No log | 1.0 | 107 | 2.0122 | 27.3045 | 15.4416 |
| No log | 2.0 | 214 | 1.8166 | 32.1348 | 15.285 |
| No log | 3.0 | 321 | 1.7273 | 32.6473 | 15.4603 |
| No log | 4.0 | 428 | 1.6669 | 32.8528 | 15.514 |
| 1.9696 | 5.0 | 535 | 1.6214 | 33.6367 | 15.507 |
| 1.9696 | 6.0 | 642 | 1.5815 | 33.5927 | 15.4743 |
| 1.9696 | 7.0 | 749 | 1.5481 | 34.0762 | 15.5 |
| 1.9696 | 8.0 | 856 | 1.5236 | 34.3891 | 15.4416 |
| 1.9696 | 9.0 | 963 | 1.4948 | 34.0203 | 15.4673 |
| 1.56 | 10.0 | 1070 | 1.4733 | 33.9927 | 15.4416 |
| 1.56 | 11.0 | 1177 | 1.4559 | 34.468 | 15.3972 |
| 1.56 | 12.0 | 1284 | 1.4334 | 34.3625 | 15.3785 |
| 1.56 | 13.0 | 1391 | 1.4167 | 34.721 | 15.3388 |
| 1.56 | 14.0 | 1498 | 1.4017 | 34.7409 | 15.4136 |
| 1.4159 | 15.0 | 1605 | 1.3886 | 34.7995 | 15.3738 |
| 1.4159 | 16.0 | 1712 | 1.3733 | 34.7944 | 15.3879 |
| 1.4159 | 17.0 | 1819 | 1.3627 | 35.0969 | 15.4089 |
| 1.4159 | 18.0 | 1926 | 1.3517 | 35.157 | 15.3505 |
| 1.3203 | 19.0 | 2033 | 1.3452 | 34.9134 | 15.2126 |
| 1.3203 | 20.0 | 2140 | 1.3325 | 35.5535 | 15.3084 |
| 1.3203 | 21.0 | 2247 | 1.3268 | 35.9899 | 15.2056 |
| 1.3203 | 22.0 | 2354 | 1.3163 | 36.1116 | 15.243 |
| 1.3203 | 23.0 | 2461 | 1.3115 | 36.2296 | 15.1752 |
| 1.2505 | 24.0 | 2568 | 1.3038 | 36.5635 | 15.2056 |
| 1.2505 | 25.0 | 2675 | 1.2996 | 36.7848 | 15.2243 |
| 1.2505 | 26.0 | 2782 | 1.2914 | 36.3015 | 15.2336 |
| 1.2505 | 27.0 | 2889 | 1.2856 | 36.73 | 15.2664 |
| 1.2505 | 28.0 | 2996 | 1.2810 | 36.8486 | 15.2897 |
| 1.1949 | 29.0 | 3103 | 1.2780 | 37.1042 | 15.243 |
| 1.1949 | 30.0 | 3210 | 1.2729 | 37.1394 | 15.2617 |
| 1.1949 | 31.0 | 3317 | 1.2673 | 36.9584 | 15.2967 |
| 1.1949 | 32.0 | 3424 | 1.2637 | 37.4488 | 15.2547 |
| 1.156 | 33.0 | 3531 | 1.2607 | 37.3112 | 15.278 |
| 1.156 | 34.0 | 3638 | 1.2573 | 37.5048 | 15.2313 |
| 1.156 | 35.0 | 3745 | 1.2532 | 37.4771 | 15.2967 |
| 1.156 | 36.0 | 3852 | 1.2512 | 37.4967 | 15.3014 |
| 1.156 | 37.0 | 3959 | 1.2494 | 37.5326 | 15.236 |
| 1.1272 | 38.0 | 4066 | 1.2470 | 37.5807 | 15.2266 |
| 1.1272 | 39.0 | 4173 | 1.2455 | 37.5478 | 15.229 |
| 1.1272 | 40.0 | 4280 | 1.2435 | 37.7117 | 15.236 |
| 1.1272 | 41.0 | 4387 | 1.2402 | 37.3874 | 15.2547 |
| 1.1272 | 42.0 | 4494 | 1.2389 | 37.584 | 15.243 |
| 1.11 | 43.0 | 4601 | 1.2377 | 37.5384 | 15.2336 |
| 1.11 | 44.0 | 4708 | 1.2364 | 37.5339 | 15.2453 |
| 1.11 | 45.0 | 4815 | 1.2362 | 37.5626 | 15.229 |
| 1.11 | 46.0 | 4922 | 1.2355 | 37.518 | 15.222 |
| 1.0999 | 47.0 | 5029 | 1.2343 | 37.5847 | 15.243 |
| 1.0999 | 48.0 | 5136 | 1.2339 | 37.5871 | 15.2313 |
| 1.0999 | 49.0 | 5243 | 1.2338 | 37.5592 | 15.236 |
| 1.0999 | 50.0 | 5350 | 1.2337 | 37.5629 | 15.215 |
### Framework versions
- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.3
- Tokenizers 0.13.3