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---
license: apache-2.0
base_model: google/t5-v1_1-large
tags:
- generated_from_trainer
model-index:
- name: Sentiment-google-t5-v1_1-large-inter_model-sorted-human_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. -->
# Sentiment-google-t5-v1_1-large-inter_model-sorted-human_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: 2.4023
## 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 |
|:-------------:|:-----:|:----:|:---------------:|
| 21.0529 | 1.0 | 44 | 22.8438 |
| 19.8705 | 2.0 | 88 | 18.5102 |
| 15.6787 | 3.0 | 132 | 12.3789 |
| 12.2348 | 4.0 | 176 | 11.0309 |
| 10.1559 | 5.0 | 220 | 10.6052 |
| 9.7633 | 6.0 | 264 | 10.3095 |
| 9.6742 | 7.0 | 308 | 10.2322 |
| 9.5533 | 8.0 | 352 | 10.1060 |
| 9.1403 | 9.0 | 396 | 9.6300 |
| 8.592 | 10.0 | 440 | 9.1220 |
| 8.4005 | 11.0 | 484 | 8.8250 |
| 8.2765 | 12.0 | 528 | 8.6542 |
| 7.9206 | 13.0 | 572 | 8.5108 |
| 1.7776 | 14.0 | 616 | 0.9630 |
| 0.9247 | 15.0 | 660 | 0.8549 |
| 0.9119 | 16.0 | 704 | 0.8479 |
| 0.9041 | 17.0 | 748 | 0.8443 |
| 0.9051 | 18.0 | 792 | 0.8442 |
| 0.8938 | 19.0 | 836 | 0.8585 |
| 0.8868 | 20.0 | 880 | 0.8510 |
| 0.8859 | 21.0 | 924 | 0.8462 |
| 0.8982 | 22.0 | 968 | 0.8460 |
| 0.8848 | 23.0 | 1012 | 0.8481 |
### Framework versions
- Transformers 4.34.0
- Pytorch 2.1.0+cu121
- Datasets 2.14.5
- Tokenizers 0.14.1
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