File size: 3,467 Bytes
3e88e51 e3099ec 3e88e51 e3099ec 3e88e51 e3099ec 3e88e51 e3099ec 3e88e51 | 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 82 83 84 85 86 87 | ---
library_name: transformers
license: mit
base_model: FacebookAI/roberta-large
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: roberta-Reflections-goodareas-sweeps-current
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. -->
# roberta-Reflections-goodareas-sweeps-current
This model is a fine-tuned version of [FacebookAI/roberta-large](https://huggingface.co/FacebookAI/roberta-large) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1937
- Accuracy: 0.8562
- Precision: 0.3984
- Recall: 0.5632
- F1: 0.4667
## 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: 3.693911058164899e-06
- train_batch_size: 32
- eval_batch_size: 16
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 20
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 0.3925 | 1.0 | 52 | 0.1759 | 0.8883 | 0.0 | 0.0 | 0.0 |
| 0.3241 | 2.0 | 104 | 0.1606 | 0.8883 | 0.0 | 0.0 | 0.0 |
| 0.2914 | 3.0 | 156 | 0.1744 | 0.8883 | 0.0 | 0.0 | 0.0 |
| 0.2821 | 4.0 | 208 | 0.2609 | 0.8909 | 0.75 | 0.0345 | 0.0659 |
| 0.2739 | 5.0 | 260 | 0.1763 | 0.8935 | 0.75 | 0.0690 | 0.1263 |
| 0.2533 | 6.0 | 312 | 0.1390 | 0.8922 | 0.6154 | 0.0920 | 0.16 |
| 0.2482 | 7.0 | 364 | 0.2199 | 0.8755 | 0.4490 | 0.5057 | 0.4757 |
| 0.2362 | 8.0 | 416 | 0.2124 | 0.8652 | 0.4286 | 0.6207 | 0.5070 |
| 0.2375 | 9.0 | 468 | 0.1351 | 0.8973 | 0.5614 | 0.3678 | 0.4444 |
| 0.228 | 10.0 | 520 | 0.1650 | 0.8870 | 0.4945 | 0.5172 | 0.5056 |
| 0.2212 | 11.0 | 572 | 0.1771 | 0.8845 | 0.4851 | 0.5632 | 0.5213 |
| 0.2217 | 12.0 | 624 | 0.1756 | 0.8832 | 0.4792 | 0.5287 | 0.5027 |
| 0.2109 | 13.0 | 676 | 0.1942 | 0.8614 | 0.4118 | 0.5632 | 0.4757 |
| 0.2018 | 14.0 | 728 | 0.1795 | 0.8678 | 0.4298 | 0.5632 | 0.4876 |
| 0.2013 | 15.0 | 780 | 0.1817 | 0.8652 | 0.4211 | 0.5517 | 0.4776 |
| 0.1943 | 16.0 | 832 | 0.2071 | 0.8575 | 0.4077 | 0.6092 | 0.4885 |
| 0.2023 | 17.0 | 884 | 0.2143 | 0.8498 | 0.3897 | 0.6092 | 0.4753 |
| 0.1924 | 18.0 | 936 | 0.1966 | 0.8562 | 0.4031 | 0.5977 | 0.4815 |
| 0.183 | 19.0 | 988 | 0.1914 | 0.8614 | 0.4118 | 0.5632 | 0.4757 |
| 0.191 | 20.0 | 1040 | 0.1937 | 0.8562 | 0.3984 | 0.5632 | 0.4667 |
### Framework versions
- Transformers 4.48.3
- Pytorch 2.5.1+cu124
- Datasets 2.21.0
- Tokenizers 0.21.0
|