File size: 2,347 Bytes
3e7c247 |
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 |
---
language:
- en
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- top_v2
model-index:
- name: t5-base-pointer-adv-top_v2
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-base-pointer-adv-top_v2
This model is a fine-tuned version of [google/mt5-base](https://huggingface.co/google/mt5-base) on the top_v2 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0255
- Exact Match: 0.8472
## 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: 0.001
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 64
- total_train_batch_size: 512
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- training_steps: 3000
### Training results
| Training Loss | Epoch | Step | Validation Loss | Exact Match |
|:-------------:|:-----:|:----:|:---------------:|:-----------:|
| 2.2938 | 0.41 | 200 | 0.5532 | 0.0012 |
| 0.671 | 0.82 | 400 | 0.1624 | 0.1610 |
| 0.5276 | 1.23 | 600 | 0.0692 | 0.2157 |
| 0.4196 | 1.64 | 800 | 0.0491 | 0.2259 |
| 0.3593 | 2.05 | 1000 | 0.0400 | 0.2291 |
| 0.3471 | 2.46 | 1200 | 0.0335 | 0.2297 |
| 0.3416 | 2.87 | 1400 | 0.0307 | 0.2318 |
| 0.3351 | 3.29 | 1600 | 0.0307 | 0.2334 |
| 0.3316 | 3.7 | 1800 | 0.0297 | 0.2343 |
| 0.3312 | 4.11 | 2000 | 0.0282 | 0.2344 |
| 0.3271 | 4.52 | 2200 | 0.0262 | 0.2365 |
| 0.3241 | 4.93 | 2400 | 0.0263 | 0.2365 |
| 0.3227 | 5.34 | 2600 | 0.0259 | 0.2368 |
| 0.3201 | 5.75 | 2800 | 0.0257 | 0.2365 |
| 0.3227 | 6.16 | 3000 | 0.0255 | 0.2365 |
### Framework versions
- Transformers 4.24.0
- Pytorch 1.13.0+cu117
- Datasets 2.7.0
- Tokenizers 0.13.2
|