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---
license: apache-2.0
base_model: t5-base
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
model-index:
- name: t5-base_sst2_dense_epochs-8
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: glue
type: glue
config: sst2
split: validation
args: sst2
metrics:
- name: Accuracy
type: accuracy
value: 0.9231651376146789
---
<!-- 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. -->
# t5-base_sst2_dense_epochs-8
This model is a fine-tuned version of [t5-base](https://huggingface.co/t5-base) on the glue dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2179
- Accuracy: 0.9232
## 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: 32
- eval_batch_size: 64
- seed: 0
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 20
- num_epochs: 8
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.6384 | 0.02 | 50 | 0.6360 | 0.7064 |
| 0.3416 | 0.05 | 100 | 0.2955 | 0.8922 |
| 0.29 | 0.07 | 150 | 0.2512 | 0.9094 |
| 0.2371 | 0.1 | 200 | 0.2511 | 0.9106 |
| 0.2059 | 0.12 | 250 | 0.2379 | 0.9174 |
| 0.2617 | 0.14 | 300 | 0.2299 | 0.9174 |
| 0.2266 | 0.17 | 350 | 0.2190 | 0.9243 |
| 0.2288 | 0.19 | 400 | 0.2292 | 0.9255 |
| 0.2385 | 0.21 | 450 | 0.2263 | 0.9232 |
| 0.161 | 0.24 | 500 | 0.2368 | 0.9243 |
| 0.158 | 0.26 | 550 | 0.2411 | 0.9174 |
| 0.2469 | 0.29 | 600 | 0.2381 | 0.9209 |
| 0.2417 | 0.31 | 650 | 0.2349 | 0.9163 |
| 0.1614 | 0.33 | 700 | 0.2251 | 0.9174 |
| 0.2764 | 0.36 | 750 | 0.2129 | 0.9266 |
| 0.1499 | 0.38 | 800 | 0.2248 | 0.9197 |
| 0.1376 | 0.4 | 850 | 0.2285 | 0.9232 |
| 0.1875 | 0.43 | 900 | 0.2324 | 0.9312 |
| 0.1819 | 0.45 | 950 | 0.2302 | 0.9220 |
| 0.2373 | 0.48 | 1000 | 0.2179 | 0.9232 |
| 0.0956 | 0.5 | 1050 | 0.2077 | 0.9278 |
| 0.2396 | 0.52 | 1100 | 0.3249 | 0.9266 |
| 0.2543 | 0.55 | 1150 | 0.4440 | 0.9243 |
| 0.0942 | 0.57 | 1200 | 0.1982 | 0.9312 |
| 0.1296 | 0.59 | 1250 | 0.4270 | 0.9335 |
| 0.1618 | 0.62 | 1300 | 0.1893 | 0.9392 |
| 0.1902 | 0.64 | 1350 | 0.1911 | 0.9381 |
| 0.1234 | 0.67 | 1400 | 0.1903 | 0.9346 |
| 0.1369 | 0.69 | 1450 | 0.4157 | 0.9335 |
| 0.1149 | 0.71 | 1500 | 0.4121 | 0.9323 |
| 0.1501 | 0.74 | 1550 | 0.6343 | 0.9358 |
| 0.1679 | 0.76 | 1600 | 0.5294 | 0.9323 |
| 0.1462 | 0.78 | 1650 | 0.4037 | 0.9392 |
| 0.2111 | 0.81 | 1700 | 0.4094 | 0.9323 |
| 0.0902 | 0.83 | 1750 | 0.4094 | 0.9346 |
| 0.1185 | 0.86 | 1800 | 0.4059 | 0.9323 |
| 0.1602 | 0.88 | 1850 | 0.2946 | 0.9323 |
| 0.1212 | 0.9 | 1900 | 0.3037 | 0.9312 |
### Framework versions
- Transformers 4.34.1
- Pytorch 2.0.1+cu117
- Datasets 2.9.0
- Tokenizers 0.14.1
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