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---
license: apache-2.0
base_model: t5-base
tags:
- generated_from_trainer
datasets:
- sst
model-index:
- name: sst-t5-base
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. -->
# sst-t5-base
This model is a fine-tuned version of [t5-base](https://huggingface.co/t5-base) on the sst dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0185
- Mse: 0.0185
## 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: 5e-05
- train_batch_size: 8
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- 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 | Mse |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| No log | 1.0 | 267 | 0.0196 | 0.0196 |
| 0.0237 | 2.0 | 534 | 0.0179 | 0.0179 |
| 0.0237 | 3.0 | 801 | 0.0174 | 0.0174 |
| 0.0133 | 4.0 | 1068 | 0.0182 | 0.0182 |
| 0.0133 | 5.0 | 1335 | 0.0181 | 0.0181 |
| 0.0101 | 6.0 | 1602 | 0.0180 | 0.0180 |
| 0.0101 | 7.0 | 1869 | 0.0183 | 0.0183 |
| 0.0083 | 8.0 | 2136 | 0.0188 | 0.0188 |
| 0.0083 | 9.0 | 2403 | 0.0185 | 0.0186 |
| 0.0067 | 10.0 | 2670 | 0.0187 | 0.0187 |
| 0.0067 | 11.0 | 2937 | 0.0184 | 0.0184 |
| 0.0057 | 12.0 | 3204 | 0.0186 | 0.0186 |
| 0.0057 | 13.0 | 3471 | 0.0194 | 0.0194 |
| 0.005 | 14.0 | 3738 | 0.0175 | 0.0176 |
| 0.0045 | 15.0 | 4005 | 0.0182 | 0.0182 |
| 0.0045 | 16.0 | 4272 | 0.0183 | 0.0183 |
| 0.0041 | 17.0 | 4539 | 0.0187 | 0.0187 |
| 0.0041 | 18.0 | 4806 | 0.0186 | 0.0186 |
| 0.0038 | 19.0 | 5073 | 0.0188 | 0.0188 |
| 0.0038 | 20.0 | 5340 | 0.0185 | 0.0185 |
### Framework versions
- Transformers 4.37.0
- Pytorch 1.13.1+cu117
- Datasets 2.15.0
- Tokenizers 0.15.2
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