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---
license: apache-2.0
base_model: google/long-t5-tglobal-base
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: Word-selector
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. -->
# Word-selector
This model is a fine-tuned version of [google/long-t5-tglobal-base](https://huggingface.co/google/long-t5-tglobal-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 2.1303
- Rouge1: 0.3216
- Rouge2: 0.0621
- Rougel: 0.2469
- Rougelsum: 0.2469
- Gen Len: 48.8488
## 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: 0.0002
- train_batch_size: 16
- eval_batch_size: 12
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20
### Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
| No log | 1.0 | 400 | 2.2490 | 0.1594 | 0.0161 | 0.1319 | 0.1321 | 69.2094 |
| 2.7083 | 2.0 | 800 | 2.1665 | 0.2025 | 0.0287 | 0.1648 | 0.1647 | 69.5888 |
| 2.369 | 3.0 | 1200 | 2.1296 | 0.2381 | 0.0344 | 0.1878 | 0.1878 | 57.9775 |
| 2.2185 | 4.0 | 1600 | 2.0890 | 0.2525 | 0.0399 | 0.1986 | 0.1984 | 60.2588 |
| 2.1014 | 5.0 | 2000 | 2.0731 | 0.2795 | 0.0484 | 0.2199 | 0.2199 | 49.5737 |
| 2.1014 | 6.0 | 2400 | 2.0601 | 0.2862 | 0.0525 | 0.2249 | 0.2246 | 54.4206 |
| 1.9992 | 7.0 | 2800 | 2.0592 | 0.3004 | 0.0533 | 0.2351 | 0.2351 | 49.9325 |
| 1.9232 | 8.0 | 3200 | 2.0529 | 0.3033 | 0.0558 | 0.2366 | 0.2368 | 49.8744 |
| 1.8534 | 9.0 | 3600 | 2.0600 | 0.3024 | 0.0573 | 0.2366 | 0.2366 | 50.355 |
| 1.795 | 10.0 | 4000 | 2.0715 | 0.3082 | 0.0561 | 0.2392 | 0.2392 | 47.2162 |
| 1.795 | 11.0 | 4400 | 2.0657 | 0.3137 | 0.0595 | 0.2437 | 0.2439 | 50.3438 |
| 1.73 | 12.0 | 4800 | 2.0759 | 0.3142 | 0.0597 | 0.2434 | 0.2433 | 51.1619 |
| 1.6844 | 13.0 | 5200 | 2.0818 | 0.3172 | 0.0605 | 0.2458 | 0.2458 | 48.9956 |
| 1.6398 | 14.0 | 5600 | 2.0942 | 0.3149 | 0.0599 | 0.2428 | 0.243 | 47.3812 |
| 1.6063 | 15.0 | 6000 | 2.1047 | 0.3171 | 0.0609 | 0.243 | 0.243 | 51.685 |
| 1.6063 | 16.0 | 6400 | 2.1095 | 0.3234 | 0.0622 | 0.248 | 0.248 | 50.1588 |
| 1.5659 | 17.0 | 6800 | 2.1180 | 0.3212 | 0.0627 | 0.2479 | 0.2478 | 49.0894 |
| 1.5456 | 18.0 | 7200 | 2.1212 | 0.3208 | 0.0616 | 0.2455 | 0.2456 | 48.8688 |
| 1.5177 | 19.0 | 7600 | 2.1275 | 0.3214 | 0.0628 | 0.2467 | 0.2467 | 48.4125 |
| 1.5161 | 20.0 | 8000 | 2.1303 | 0.3216 | 0.0621 | 0.2469 | 0.2469 | 48.8488 |
### Framework versions
- Transformers 4.37.2
- Pytorch 2.1.1+cu121
- Datasets 3.0.1
- Tokenizers 0.15.1
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