File size: 2,669 Bytes
30b38c4 d33d866 30b38c4 eeacd1a 30b38c4 eeacd1a 30b38c4 e58afb8 30b38c4 e58afb8 |
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 |
---
license: apache-2.0
tags:
- generated_from_trainer
model-index:
- name: t5-end2end-questions-generation-cvqualtrics-squad-V1
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. -->
# t5-end2end-questions-generation-cvqualtrics-squad-V1
## Model description
This model is a fine-tuned version of [t5-base](https://huggingface.co/t5-base) on the Custom Domain-Specific dataset.
It achieves the following results on the evaluation set:
- Loss: 1.2337
### Framework versions
- Transformers 4.21.0
- Pytorch 1.12.0+cu113
- Datasets 2.4.0
- Tokenizers 0.12.1
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 0.0001
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 2.6162 | 0.34 | 100 | 1.8890 |
| 1.9995 | 0.67 | 200 | 1.6871 |
| 1.8697 | 1.01 | 300 | 1.6146 |
| 1.7682 | 1.34 | 400 | 1.5530 |
| 1.7323 | 1.68 | 500 | 1.5232 |
| 1.7256 | 2.01 | 600 | 1.4921 |
| 1.6506 | 2.35 | 700 | 1.4640 |
| 1.6438 | 2.68 | 800 | 1.4406 |
| 1.6399 | 3.02 | 900 | 1.4137 |
| 1.5786 | 3.36 | 1000 | 1.3924 |
| 1.5805 | 3.69 | 1100 | 1.3788 |
| 1.5824 | 4.03 | 1200 | 1.3626 |
| 1.5295 | 4.36 | 1300 | 1.3454 |
| 1.5333 | 4.7 | 1400 | 1.3356 |
| 1.537 | 5.03 | 1500 | 1.3230 |
| 1.5002 | 5.37 | 1600 | 1.3157 |
| 1.4936 | 5.7 | 1700 | 1.3046 |
| 1.4937 | 6.04 | 1800 | 1.2958 |
| 1.4649 | 6.38 | 1900 | 1.2826 |
| 1.4742 | 6.71 | 2000 | 1.2744 |
| 1.4641 | 7.05 | 2100 | 1.2603 |
| 1.4472 | 7.38 | 2200 | 1.2595 |
| 1.4403 | 7.72 | 2300 | 1.2526 |
| 1.4508 | 8.05 | 2400 | 1.2475 |
| 1.4191 | 8.39 | 2500 | 1.2412 |
| 1.4367 | 8.72 | 2600 | 1.2354 |
| 1.4272 | 9.06 | 2700 | 1.2386 |
| 1.4104 | 9.4 | 2800 | 1.2323 |
| 1.4179 | 9.73 | 2900 | 1.2337 |
|