File size: 3,033 Bytes
33391a0 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 |
---
license: apache-2.0
base_model: google/t5-v1_1-large
tags:
- generated_from_trainer
model-index:
- name: Sentiment-google-t5-v1_1-large-intra_model-frequency-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-intra_model-frequency-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: 1.5938
## 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 |
|:-------------:|:-----:|:----:|:---------------:|
| 20.8407 | 1.0 | 44 | 24.0718 |
| 19.0527 | 2.0 | 88 | 19.4828 |
| 13.4842 | 3.0 | 132 | 11.5393 |
| 10.8626 | 4.0 | 176 | 10.8995 |
| 10.3562 | 5.0 | 220 | 10.7412 |
| 10.008 | 6.0 | 264 | 10.5271 |
| 9.8519 | 7.0 | 308 | 10.3934 |
| 9.6414 | 8.0 | 352 | 10.0350 |
| 8.9978 | 9.0 | 396 | 9.4410 |
| 8.6735 | 10.0 | 440 | 9.0569 |
| 8.3986 | 11.0 | 484 | 8.8689 |
| 8.2999 | 12.0 | 528 | 8.7266 |
| 1.7304 | 13.0 | 572 | 1.1034 |
| 1.165 | 14.0 | 616 | 1.0495 |
| 1.0776 | 15.0 | 660 | 1.0454 |
| 1.0862 | 16.0 | 704 | 1.0384 |
| 1.0628 | 17.0 | 748 | 1.0318 |
| 1.0547 | 18.0 | 792 | 1.0329 |
| 1.0513 | 19.0 | 836 | 1.0381 |
| 1.0389 | 20.0 | 880 | 1.0247 |
| 1.0381 | 21.0 | 924 | 1.0231 |
| 1.056 | 22.0 | 968 | 1.0160 |
| 1.0508 | 23.0 | 1012 | 1.0171 |
| 1.0514 | 24.0 | 1056 | 1.0143 |
| 1.0373 | 25.0 | 1100 | 1.0128 |
| 1.0295 | 26.0 | 1144 | 1.0129 |
| 1.0178 | 27.0 | 1188 | 1.0110 |
| 1.0216 | 28.0 | 1232 | 1.0056 |
| 1.0355 | 29.0 | 1276 | 1.0084 |
| 1.0276 | 30.0 | 1320 | 1.0017 |
| 1.0066 | 31.0 | 1364 | 1.0080 |
| 1.0107 | 32.0 | 1408 | 1.0044 |
| 1.0165 | 33.0 | 1452 | 1.0019 |
### Framework versions
- Transformers 4.34.0
- Pytorch 2.1.0+cu121
- Datasets 2.6.1
- Tokenizers 0.14.1
|