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---
license: apache-2.0
base_model: google/t5-v1_1-large
tags:
- generated_from_trainer
model-index:
- name: ghc-google-t5-v1_1-large-intra_model-dataset-frequency-model_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. -->
# ghc-google-t5-v1_1-large-intra_model-dataset-frequency-model_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: nan
## 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: 32
- eval_batch_size: 32
- 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 |
|:-------------:|:-----:|:-----:|:---------------:|
| 6.1892 | 1.0 | 345 | 6.6229 |
| 5.2951 | 2.0 | 690 | 5.5307 |
| 0.2702 | 3.0 | 1035 | 0.2511 |
| 0.2605 | 4.0 | 1380 | 0.2295 |
| 0.2635 | 5.0 | 1725 | 0.2378 |
| 0.2405 | 6.0 | 2070 | 0.2250 |
| 0.2605 | 7.0 | 2415 | 0.2226 |
| 0.2235 | 8.0 | 2760 | 0.2237 |
| 0.2303 | 9.0 | 3105 | 0.2199 |
| 0.2378 | 10.0 | 3450 | 0.2214 |
| 0.24 | 11.0 | 3795 | 0.2169 |
| 0.2236 | 12.0 | 4140 | 0.2183 |
| 0.2079 | 13.0 | 4485 | 0.2184 |
| 0.2594 | 14.0 | 4830 | 0.2159 |
| 0.2303 | 15.0 | 5175 | 0.2170 |
| 0.2238 | 16.0 | 5520 | 0.2146 |
| 0.2071 | 17.0 | 5865 | 0.2161 |
| 0.2129 | 18.0 | 6210 | 0.2130 |
| 0.2297 | 19.0 | 6555 | 0.2133 |
| 0.2434 | 20.0 | 6900 | 0.2158 |
| 0.2158 | 21.0 | 7245 | 0.2147 |
| 0.2222 | 22.0 | 7590 | 0.2166 |
| 0.2388 | 23.0 | 7935 | 0.2127 |
| 0.2132 | 24.0 | 8280 | 0.2123 |
| 0.2269 | 25.0 | 8625 | 0.2136 |
| 0.2237 | 26.0 | 8970 | 0.2142 |
| 0.2064 | 27.0 | 9315 | 0.2135 |
| 0.2329 | 28.0 | 9660 | 0.2140 |
| 0.2319 | 29.0 | 10005 | 0.2140 |
### Framework versions
- Transformers 4.34.0
- Pytorch 2.1.0+cu121
- Datasets 2.14.5
- Tokenizers 0.14.1
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