File size: 3,022 Bytes
3c8b24d |
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 79 80 81 |
---
library_name: transformers
license: mit
base_model: FacebookAI/roberta-base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: f0e34afffe85e814b4e41abc80263fca
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. -->
# f0e34afffe85e814b4e41abc80263fca
This model is a fine-tuned version of [FacebookAI/roberta-base](https://huggingface.co/FacebookAI/roberta-base) on the contemmcm/hate-speech-and-offensive-language dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3189
- Data Size: 1.0
- Epoch Runtime: 49.4083
- Accuracy: 0.9115
- F1 Macro: 0.7587
## 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: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- total_train_batch_size: 32
- total_eval_batch_size: 32
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: constant
- num_epochs: 50
### Training results
| Training Loss | Epoch | Step | Validation Loss | Data Size | Epoch Runtime | Accuracy | F1 Macro |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:-------------:|:--------:|:--------:|
| No log | 0 | 0 | 1.2039 | 0 | 4.1789 | 0.0601 | 0.0378 |
| No log | 1 | 619 | 0.6824 | 0.0078 | 4.7944 | 0.7672 | 0.2894 |
| No log | 2 | 1238 | 0.6033 | 0.0156 | 5.1378 | 0.7672 | 0.2894 |
| 0.0148 | 3 | 1857 | 0.3472 | 0.0312 | 5.9556 | 0.8904 | 0.5871 |
| 0.0148 | 4 | 2476 | 0.2996 | 0.0625 | 7.7942 | 0.9046 | 0.6062 |
| 0.3137 | 5 | 3095 | 0.2770 | 0.125 | 10.1123 | 0.9065 | 0.7305 |
| 0.0257 | 6 | 3714 | 0.2918 | 0.25 | 15.7152 | 0.9054 | 0.6093 |
| 0.2836 | 7 | 4333 | 0.3122 | 0.5 | 27.3986 | 0.8981 | 0.7566 |
| 0.2616 | 8.0 | 4952 | 0.2436 | 1.0 | 50.3288 | 0.9164 | 0.6985 |
| 0.2095 | 9.0 | 5571 | 0.3629 | 1.0 | 49.8399 | 0.8843 | 0.6892 |
| 0.2033 | 10.0 | 6190 | 0.2972 | 1.0 | 49.5511 | 0.9150 | 0.7817 |
| 0.2164 | 11.0 | 6809 | 0.2992 | 1.0 | 50.8395 | 0.9093 | 0.7611 |
| 0.1258 | 12.0 | 7428 | 0.3189 | 1.0 | 49.4083 | 0.9115 | 0.7587 |
### Framework versions
- Transformers 4.57.0
- Pytorch 2.8.0+cu128
- Datasets 4.3.0
- Tokenizers 0.22.1
|