vg055 commited on
Commit
c00d12c
1 Parent(s): 3e23b30

update model card README.md

Browse files
Files changed (1) hide show
  1. README.md +62 -0
README.md ADDED
@@ -0,0 +1,62 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ license: mit
3
+ tags:
4
+ - generated_from_trainer
5
+ metrics:
6
+ - f1
7
+ model-index:
8
+ - name: multilingual-e5-large-finetuned-IberAuTexTification2024-7030-4epo-task1-v2
9
+ results: []
10
+ ---
11
+
12
+ <!-- This model card has been generated automatically according to the information the Trainer had access to. You
13
+ should probably proofread and complete it, then remove this comment. -->
14
+
15
+ # multilingual-e5-large-finetuned-IberAuTexTification2024-7030-4epo-task1-v2
16
+
17
+ This model is a fine-tuned version of [intfloat/multilingual-e5-large](https://huggingface.co/intfloat/multilingual-e5-large) on the None dataset.
18
+ It achieves the following results on the evaluation set:
19
+ - Loss: 0.1903
20
+ - F1: 0.9662
21
+
22
+ ## Model description
23
+
24
+ More information needed
25
+
26
+ ## Intended uses & limitations
27
+
28
+ More information needed
29
+
30
+ ## Training and evaluation data
31
+
32
+ More information needed
33
+
34
+ ## Training procedure
35
+
36
+ ### Training hyperparameters
37
+
38
+ The following hyperparameters were used during training:
39
+ - learning_rate: 2e-05
40
+ - train_batch_size: 16
41
+ - eval_batch_size: 16
42
+ - seed: 42
43
+ - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
44
+ - lr_scheduler_type: linear
45
+ - num_epochs: 4
46
+
47
+ ### Training results
48
+
49
+ | Training Loss | Epoch | Step | Validation Loss | F1 |
50
+ |:-------------:|:-----:|:-----:|:---------------:|:------:|
51
+ | 0.1416 | 1.0 | 4798 | 0.3054 | 0.9350 |
52
+ | 0.088 | 2.0 | 9596 | 0.1850 | 0.9628 |
53
+ | 0.0376 | 3.0 | 14394 | 0.1903 | 0.9662 |
54
+ | 0.0127 | 4.0 | 19192 | 0.2281 | 0.9648 |
55
+
56
+
57
+ ### Framework versions
58
+
59
+ - Transformers 4.28.0
60
+ - Pytorch 2.3.0+cu121
61
+ - Datasets 2.19.1
62
+ - Tokenizers 0.13.3