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---
license: apache-2.0
base_model: google/flan-t5-large
tags:
- generated_from_trainer
model-index:
- name: models
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. -->
# models
This model is a fine-tuned version of [google/flan-t5-large](https://huggingface.co/google/flan-t5-large) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1902
## 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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 2
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:------:|:-----:|:---------------:|
| 0.3389 | 0.0699 | 500 | 0.2668 |
| 0.2719 | 0.1398 | 1000 | 0.2524 |
| 0.2612 | 0.2097 | 1500 | 0.2381 |
| 0.2634 | 0.2796 | 2000 | 0.2313 |
| 0.2403 | 0.3495 | 2500 | 0.2260 |
| 0.2433 | 0.4193 | 3000 | 0.2190 |
| 0.2351 | 0.4892 | 3500 | 0.2168 |
| 0.2424 | 0.5591 | 4000 | 0.2109 |
| 0.2198 | 0.6290 | 4500 | 0.2071 |
| 0.2313 | 0.6989 | 5000 | 0.2062 |
| 0.226 | 0.7688 | 5500 | 0.2058 |
| 0.2195 | 0.8387 | 6000 | 0.2030 |
| 0.2173 | 0.9086 | 6500 | 0.2009 |
| 0.2359 | 0.9785 | 7000 | 0.1969 |
| 0.2055 | 1.0484 | 7500 | 0.1961 |
| 0.2074 | 1.1183 | 8000 | 0.1980 |
| 0.2066 | 1.1881 | 8500 | 0.1938 |
| 0.2077 | 1.2580 | 9000 | 0.1937 |
| 0.196 | 1.3279 | 9500 | 0.1948 |
| 0.2027 | 1.3978 | 10000 | 0.1931 |
| 0.2001 | 1.4677 | 10500 | 0.1922 |
| 0.1925 | 1.5376 | 11000 | 0.1932 |
| 0.1933 | 1.6075 | 11500 | 0.1900 |
| 0.2038 | 1.6774 | 12000 | 0.1921 |
| 0.1892 | 1.7473 | 12500 | 0.1914 |
| 0.1956 | 1.8172 | 13000 | 0.1904 |
| 0.1956 | 1.8871 | 13500 | 0.1898 |
| 0.1925 | 1.9569 | 14000 | 0.1902 |
### Framework versions
- Transformers 4.40.2
- Pytorch 2.1.2
- Datasets 2.18.0
- Tokenizers 0.19.1
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