update model card README.md
Browse files
README.md
ADDED
|
@@ -0,0 +1,73 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
---
|
| 2 |
+
tags:
|
| 3 |
+
- generated_from_trainer
|
| 4 |
+
metrics:
|
| 5 |
+
- precision
|
| 6 |
+
- recall
|
| 7 |
+
- f1
|
| 8 |
+
- accuracy
|
| 9 |
+
model-index:
|
| 10 |
+
- name: Longformer_v5
|
| 11 |
+
results: []
|
| 12 |
+
---
|
| 13 |
+
|
| 14 |
+
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
|
| 15 |
+
should probably proofread and complete it, then remove this comment. -->
|
| 16 |
+
|
| 17 |
+
# Longformer_v5
|
| 18 |
+
|
| 19 |
+
This model is a fine-tuned version of [allenai/longformer-base-4096](https://huggingface.co/allenai/longformer-base-4096) on the None dataset.
|
| 20 |
+
It achieves the following results on the evaluation set:
|
| 21 |
+
- Loss: 0.7919
|
| 22 |
+
- Precision: 0.8516
|
| 23 |
+
- Recall: 0.8678
|
| 24 |
+
- F1: 0.6520
|
| 25 |
+
- Accuracy: 0.8259
|
| 26 |
+
|
| 27 |
+
## Model description
|
| 28 |
+
|
| 29 |
+
More information needed
|
| 30 |
+
|
| 31 |
+
## Intended uses & limitations
|
| 32 |
+
|
| 33 |
+
More information needed
|
| 34 |
+
|
| 35 |
+
## Training and evaluation data
|
| 36 |
+
|
| 37 |
+
More information needed
|
| 38 |
+
|
| 39 |
+
## Training procedure
|
| 40 |
+
|
| 41 |
+
### Training hyperparameters
|
| 42 |
+
|
| 43 |
+
The following hyperparameters were used during training:
|
| 44 |
+
- learning_rate: 5e-05
|
| 45 |
+
- train_batch_size: 1
|
| 46 |
+
- eval_batch_size: 1
|
| 47 |
+
- seed: 42
|
| 48 |
+
- gradient_accumulation_steps: 8
|
| 49 |
+
- total_train_batch_size: 8
|
| 50 |
+
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
|
| 51 |
+
- lr_scheduler_type: linear
|
| 52 |
+
- lr_scheduler_warmup_ratio: 0.1
|
| 53 |
+
- num_epochs: 7
|
| 54 |
+
|
| 55 |
+
### Training results
|
| 56 |
+
|
| 57 |
+
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|
| 58 |
+
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
|
| 59 |
+
| 0.7744 | 1.0 | 1012 | 0.5785 | 0.8375 | 0.8501 | 0.5798 | 0.8098 |
|
| 60 |
+
| 0.5211 | 2.0 | 2024 | 0.5415 | 0.8434 | 0.8801 | 0.6251 | 0.8282 |
|
| 61 |
+
| 0.3996 | 3.0 | 3036 | 0.5565 | 0.8500 | 0.8766 | 0.6303 | 0.8274 |
|
| 62 |
+
| 0.2964 | 4.0 | 4048 | 0.6017 | 0.8617 | 0.8546 | 0.6415 | 0.8240 |
|
| 63 |
+
| 0.2187 | 5.0 | 5060 | 0.6660 | 0.8485 | 0.8718 | 0.6431 | 0.8271 |
|
| 64 |
+
| 0.1603 | 6.0 | 6072 | 0.7235 | 0.8493 | 0.8759 | 0.6544 | 0.8290 |
|
| 65 |
+
| 0.1208 | 7.0 | 7084 | 0.7919 | 0.8516 | 0.8678 | 0.6520 | 0.8259 |
|
| 66 |
+
|
| 67 |
+
|
| 68 |
+
### Framework versions
|
| 69 |
+
|
| 70 |
+
- Transformers 4.18.0
|
| 71 |
+
- Pytorch 1.10.0+cu111
|
| 72 |
+
- Datasets 2.1.0
|
| 73 |
+
- Tokenizers 0.12.1
|