Cheng98 commited on
Commit
57480d7
1 Parent(s): 26062fe

update model card README.md

Browse files
Files changed (1) hide show
  1. README.md +65 -0
README.md ADDED
@@ -0,0 +1,65 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ license: apache-2.0
3
+ base_model: JackFram/llama-160m
4
+ tags:
5
+ - generated_from_trainer
6
+ metrics:
7
+ - accuracy
8
+ model-index:
9
+ - name: llama-160m-qqp
10
+ results: []
11
+ ---
12
+
13
+ <!-- This model card has been generated automatically according to the information the Trainer had access to. You
14
+ should probably proofread and complete it, then remove this comment. -->
15
+
16
+ # llama-160m-qqp
17
+
18
+ This model is a fine-tuned version of [JackFram/llama-160m](https://huggingface.co/JackFram/llama-160m) on an unknown dataset.
19
+ It achieves the following results on the evaluation set:
20
+ - Loss: 0.5816
21
+ - Accuracy: 0.6842
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: 5e-05
41
+ - train_batch_size: 16
42
+ - eval_batch_size: 32
43
+ - seed: 42
44
+ - gradient_accumulation_steps: 8
45
+ - total_train_batch_size: 128
46
+ - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
47
+ - lr_scheduler_type: linear
48
+ - num_epochs: 4
49
+
50
+ ### Training results
51
+
52
+ | Training Loss | Epoch | Step | Validation Loss | Accuracy |
53
+ |:-------------:|:-----:|:-----:|:---------------:|:--------:|
54
+ | 0.6019 | 1.0 | 2842 | 0.5971 | 0.6734 |
55
+ | 0.5849 | 2.0 | 5685 | 0.5836 | 0.6843 |
56
+ | 0.5819 | 3.0 | 8527 | 0.5815 | 0.6855 |
57
+ | 0.5768 | 4.0 | 11368 | 0.5816 | 0.6842 |
58
+
59
+
60
+ ### Framework versions
61
+
62
+ - Transformers 4.31.0
63
+ - Pytorch 2.0.1+cu117
64
+ - Datasets 2.18.0
65
+ - Tokenizers 0.13.3