File size: 2,080 Bytes
b8a0c10 fa392c2 b8a0c10 fa392c2 b8a0c10 fa392c2 b8a0c10 fa392c2 b8a0c10 be228a6 b8a0c10 |
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 |
---
library_name: transformers
tags:
- generated_from_trainer
datasets:
- Hartunka/processed_wikitext-103-raw-v1-rand-100_v2
metrics:
- accuracy
model-index:
- name: bert_base_rand_100_v2
results:
- task:
name: Masked Language Modeling
type: fill-mask
dataset:
name: Hartunka/processed_wikitext-103-raw-v1-rand-100_v2
type: Hartunka/processed_wikitext-103-raw-v1-rand-100_v2
metrics:
- name: Accuracy
type: accuracy
value: 0.15335932643950953
---
<!-- 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_rand_100_v2
This model is a fine-tuned version of [](https://huggingface.co/) on the Hartunka/processed_wikitext-103-raw-v1-rand-100_v2 dataset.
It achieves the following results on the evaluation set:
- Loss: 10.7777
- Accuracy: 0.1534
## 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: 0.0001
- train_batch_size: 96
- eval_batch_size: 96
- seed: 10
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 10000
- num_epochs: 25
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-------:|:-----:|:---------------:|:--------:|
| 10.6199 | 4.1982 | 10000 | 10.7772 | 0.1509 |
| 9.3028 | 8.3963 | 20000 | 11.4804 | 0.1521 |
| 7.6531 | 12.5945 | 30000 | 12.8492 | 0.1543 |
| 6.6672 | 16.7926 | 40000 | 13.9831 | 0.1512 |
| 6.3804 | 20.9908 | 50000 | 14.2044 | 0.1516 |
### Framework versions
- Transformers 4.50.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.21.1
|