File size: 1,816 Bytes
ead7327
 
714f123
ead7327
 
b47237d
 
 
ead7327
 
 
 
 
 
 
 
 
 
714f123
b47237d
2e555fd
 
 
ead7327
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
5dc91da
b47237d
 
ead7327
 
 
53fd912
2e555fd
ead7327
b47237d
 
 
 
2e555fd
 
 
b47237d
 
ead7327
 
 
b47237d
ead7327
 
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
---

license: apache-2.0
base_model: distilbert/distilbert-base-uncased-finetuned-sst-2-english
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: finetuning-sentiment-analysis-model-team-28
  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. -->

# finetuning-sentiment-analysis-model-team-28

This model is a fine-tuned version of [distilbert/distilbert-base-uncased-finetuned-sst-2-english](https://huggingface.co/distilbert/distilbert-base-uncased-finetuned-sst-2-english) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5030
- Accuracy: 0.9086
- F1: 0.9401

## 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: 1e-05

- train_batch_size: 16

- eval_batch_size: 16

- seed: 42

- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08

- lr_scheduler_type: linear

- lr_scheduler_warmup_steps: 500
- num_epochs: 3



### Training results



| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |

|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|

| 0.1075        | 1.0   | 175  | 0.3345          | 0.9129   | 0.9440 |

| 0.1063        | 2.0   | 350  | 0.4080          | 0.9014   | 0.9359 |

| 0.0262        | 3.0   | 525  | 0.5030          | 0.9086   | 0.9401 |





### Framework versions



- Transformers 4.36.2

- Pytorch 2.3.0+cu121

- Datasets 2.20.0

- Tokenizers 0.15.2