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---
license: apache-2.0
base_model: google/t5-v1_1-large
tags:
- generated_from_trainer
model-index:
- name: SChem5Labels-google-t5-v1_1-large-inter_model-sorted-model_annots_str
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. -->
# SChem5Labels-google-t5-v1_1-large-inter_model-sorted-model_annots_str
This model is a fine-tuned version of [google/t5-v1_1-large](https://huggingface.co/google/t5-v1_1-large) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8994
## 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: 0.0001
- train_batch_size: 128
- eval_batch_size: 128
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 200
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 20.7228 | 1.0 | 25 | 24.7182 |
| 19.7481 | 2.0 | 50 | 23.4091 |
| 19.3221 | 3.0 | 75 | 20.7043 |
| 17.2262 | 4.0 | 100 | 15.0872 |
| 14.7272 | 5.0 | 125 | 10.1222 |
| 12.1186 | 6.0 | 150 | 9.0762 |
| 10.3305 | 7.0 | 175 | 8.7090 |
| 8.8199 | 8.0 | 200 | 8.4070 |
| 8.2346 | 9.0 | 225 | 8.2048 |
| 7.9113 | 10.0 | 250 | 8.1018 |
| 7.6524 | 11.0 | 275 | 8.0398 |
| 7.6476 | 12.0 | 300 | 7.9791 |
| 7.4487 | 13.0 | 325 | 7.8957 |
| 7.3635 | 14.0 | 350 | 7.7393 |
| 7.2677 | 15.0 | 375 | 7.4303 |
| 7.0316 | 16.0 | 400 | 7.1862 |
| 6.7999 | 17.0 | 425 | 7.0031 |
| 6.6811 | 18.0 | 450 | 6.8875 |
| 6.6207 | 19.0 | 475 | 6.8224 |
| 6.4587 | 20.0 | 500 | 6.7708 |
| 6.3888 | 21.0 | 525 | 6.7248 |
| 6.3971 | 22.0 | 550 | 6.6744 |
| 6.3969 | 23.0 | 575 | 6.3850 |
| 0.91 | 24.0 | 600 | 0.7331 |
| 0.7237 | 25.0 | 625 | 0.6588 |
| 0.6831 | 26.0 | 650 | 0.6276 |
| 0.6785 | 27.0 | 675 | 0.6266 |
| 0.6673 | 28.0 | 700 | 0.6269 |
| 0.6728 | 29.0 | 725 | 0.6230 |
| 0.6643 | 30.0 | 750 | 0.6204 |
| 0.662 | 31.0 | 775 | 0.6187 |
| 0.6664 | 32.0 | 800 | 0.6195 |
| 0.6568 | 33.0 | 825 | 0.6180 |
| 0.6453 | 34.0 | 850 | 0.6187 |
| 0.6619 | 35.0 | 875 | 0.6260 |
| 0.6539 | 36.0 | 900 | 0.6168 |
| 0.6468 | 37.0 | 925 | 0.6188 |
| 0.6567 | 38.0 | 950 | 0.6221 |
| 0.6521 | 39.0 | 975 | 0.6172 |
| 0.6403 | 40.0 | 1000 | 0.6141 |
| 0.6505 | 41.0 | 1025 | 0.6147 |
| 0.6419 | 42.0 | 1050 | 0.6174 |
| 0.6436 | 43.0 | 1075 | 0.6174 |
| 0.6381 | 44.0 | 1100 | 0.6130 |
| 0.6527 | 45.0 | 1125 | 0.6144 |
| 0.6489 | 46.0 | 1150 | 0.6129 |
| 0.6395 | 47.0 | 1175 | 0.6141 |
| 0.6483 | 48.0 | 1200 | 0.6174 |
| 0.6331 | 49.0 | 1225 | 0.6165 |
| 0.6454 | 50.0 | 1250 | 0.6141 |
| 0.6356 | 51.0 | 1275 | 0.6140 |
### Framework versions
- Transformers 4.34.0
- Pytorch 2.1.0+cu121
- Datasets 2.6.1
- Tokenizers 0.14.1
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