File size: 1,673 Bytes
dc45f8a 19d27f4 dc45f8a |
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 |
---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
base_model: muhtasham/olm-bert-tiny-december-2022
model-index:
- name: olm-bert-tiny-december-2022-target-glue-rte
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. -->
# olm-bert-tiny-december-2022-target-glue-rte
This model is a fine-tuned version of [muhtasham/olm-bert-tiny-december-2022](https://huggingface.co/muhtasham/olm-bert-tiny-december-2022) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.3103
- Accuracy: 0.5235
## 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: 3e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant
- training_steps: 5000
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.6883 | 6.41 | 500 | 0.6919 | 0.5523 |
| 0.5979 | 12.82 | 1000 | 0.8002 | 0.5271 |
| 0.4213 | 19.23 | 1500 | 1.0720 | 0.5090 |
| 0.2839 | 25.64 | 2000 | 1.3103 | 0.5235 |
### Framework versions
- Transformers 4.27.0.dev0
- Pytorch 1.13.1+cu116
- Datasets 2.9.1.dev0
- Tokenizers 0.13.2
|