File size: 2,494 Bytes
848b540 |
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 |
---
license: apache-2.0
base_model: t5-base
tags:
- generated_from_trainer
metrics:
- bleu
- wer
model-index:
- name: 100_randomization_model
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. -->
# 100_randomization_model
This model is a fine-tuned version of [t5-base](https://huggingface.co/t5-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 2.6576
- Bleu: 0.0001
- Wer: 0.9576
- Rougel: 0.119
- Gen Len: 18.9986
## 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: 2e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 2
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Bleu | Wer | Rougel | Gen Len |
|:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|:------:|:-------:|
| 2.5767 | 0.16 | 1000 | 1.6626 | 0.0001 | 0.954 | 0.1251 | 18.9985 |
| 1.9533 | 0.32 | 2000 | 1.5147 | 0.0001 | 0.9524 | 0.1284 | 18.9986 |
| 1.8318 | 0.48 | 3000 | 1.4392 | 0.0001 | 0.9518 | 0.1297 | 18.9986 |
| 1.7626 | 0.64 | 4000 | 1.3857 | 0.0001 | 0.9514 | 0.1306 | 18.9986 |
| 1.7199 | 0.8 | 5000 | 1.3553 | 0.0001 | 0.951 | 0.1312 | 18.9988 |
| 1.6727 | 0.96 | 6000 | 1.3325 | 0.0001 | 0.9507 | 0.1319 | 18.9986 |
| 1.9628 | 1.12 | 7000 | 1.8528 | 0.0001 | 0.9524 | 0.1293 | 18.9988 |
| 2.9138 | 1.28 | 8000 | 2.6299 | 0.0001 | 0.9568 | 0.1205 | 18.9986 |
| 3.5506 | 1.44 | 9000 | 2.7483 | 0.0001 | 0.958 | 0.1181 | 18.9987 |
| 3.5214 | 1.6 | 10000 | 2.7007 | 0.0001 | 0.9578 | 0.1186 | 18.9986 |
| 3.4669 | 1.76 | 11000 | 2.6699 | 0.0001 | 0.9576 | 0.1189 | 18.9986 |
| 3.4448 | 1.92 | 12000 | 2.6576 | 0.0001 | 0.9576 | 0.119 | 18.9986 |
### Framework versions
- Transformers 4.37.1
- Pytorch 2.3.0.dev20240122+cu121
- Datasets 2.16.1
- Tokenizers 0.15.1
|