patpizio commited on
Commit
6c95418
·
1 Parent(s): 676170d

Model save

Browse files
Files changed (1) hide show
  1. README.md +62 -0
README.md ADDED
@@ -0,0 +1,62 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ license: mit
3
+ base_model: xlm-roberta-base
4
+ tags:
5
+ - generated_from_trainer
6
+ model-index:
7
+ - name: xlmr-ne-en-all_shuffled-764-test1000
8
+ results: []
9
+ ---
10
+
11
+ <!-- This model card has been generated automatically according to the information the Trainer had access to. You
12
+ should probably proofread and complete it, then remove this comment. -->
13
+
14
+ # xlmr-ne-en-all_shuffled-764-test1000
15
+
16
+ This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on the None dataset.
17
+ It achieves the following results on the evaluation set:
18
+ - Loss: 0.6598
19
+ - R Squared: 0.2676
20
+ - Mae: 0.6318
21
+ - Pearson R: 0.6380
22
+
23
+ ## Model description
24
+
25
+ More information needed
26
+
27
+ ## Intended uses & limitations
28
+
29
+ More information needed
30
+
31
+ ## Training and evaluation data
32
+
33
+ More information needed
34
+
35
+ ## Training procedure
36
+
37
+ ### Training hyperparameters
38
+
39
+ The following hyperparameters were used during training:
40
+ - learning_rate: 2e-05
41
+ - train_batch_size: 16
42
+ - eval_batch_size: 16
43
+ - seed: 764
44
+ - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
45
+ - lr_scheduler_type: linear
46
+ - num_epochs: 3
47
+
48
+ ### Training results
49
+
50
+ | Training Loss | Epoch | Step | Validation Loss | R Squared | Mae | Pearson R |
51
+ |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:---------:|
52
+ | No log | 1.0 | 438 | 0.6430 | 0.2862 | 0.6416 | 0.5407 |
53
+ | 0.7301 | 2.0 | 876 | 0.6202 | 0.3116 | 0.6302 | 0.6325 |
54
+ | 0.5037 | 3.0 | 1314 | 0.6598 | 0.2676 | 0.6318 | 0.6380 |
55
+
56
+
57
+ ### Framework versions
58
+
59
+ - Transformers 4.34.1
60
+ - Pytorch 2.0.1+cu117
61
+ - Datasets 2.14.6
62
+ - Tokenizers 0.14.1