File size: 2,058 Bytes
66ebc28 18dfad4 66ebc28 1882b55 66ebc28 1882b55 66ebc28 1882b55 66ebc28 1882b55 66ebc28 |
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 |
---
tags:
- generated_from_trainer
base_model: alistvt/bert-base-uncased-pretrained-mlm-coqa-stories
model-index:
- name: bert-base-uncased-pretrain-finetuned-coqa-falt
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. -->
# bert-base-uncased-pretrain-finetuned-coqa-falt
This model is a fine-tuned version of [alistvt/bert-base-uncased-pretrained-mlm-coqa-stories](https://huggingface.co/alistvt/bert-base-uncased-pretrained-mlm-coqa-stories) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 2.8125
## 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: 1e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 4
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:-----:|:---------------:|
| 3.4039 | 0.29 | 2000 | 3.0921 |
| 3.1438 | 0.59 | 4000 | 2.8826 |
| 3.0252 | 0.88 | 6000 | 2.7885 |
| 2.7112 | 1.18 | 8000 | 2.7720 |
| 2.6703 | 1.47 | 10000 | 2.7581 |
| 2.6432 | 1.77 | 12000 | 2.7316 |
| 2.385 | 2.06 | 14000 | 2.7798 |
| 2.3314 | 2.36 | 16000 | 2.7836 |
| 2.3433 | 2.65 | 18000 | 2.7650 |
| 2.3604 | 2.95 | 20000 | 2.7585 |
| 2.2232 | 3.24 | 22000 | 2.8120 |
| 2.2094 | 3.53 | 24000 | 2.7945 |
| 2.2306 | 3.83 | 26000 | 2.8125 |
### Framework versions
- Transformers 4.15.0
- Pytorch 1.10.0+cu111
- Datasets 1.18.0
- Tokenizers 0.10.3
|