File size: 10,797 Bytes
b435e9f
 
 
 
 
 
 
 
199996f
 
 
 
 
88790af
 
0766a83
b435e9f
 
 
 
 
 
 
 
 
104a840
 
 
2e84fec
 
 
104a840
b435e9f
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
7a386c5
d5bb87a
66eab56
2fe4e83
8be3439
8cf4294
0098cfb
41704ca
82afa8e
7dcad79
6b2a182
0019718
e4017d7
8b4b722
4cfd80c
7d6108f
6694047
05ed00d
fc703ce
7086da8
fe97ba3
281f77d
658f203
120c463
d6266ab
5c3cdda
bdcec46
ce47f3b
e88a417
3126906
f56af6c
dda1a26
8ac3086
ebc3d64
f15ff1d
f1f5d77
 
02c4155
4729389
432d048
dc4ebf2
aacdec5
 
8f634bf
2261055
ef9c66b
f192211
ed2f4c1
2e84fec
104a840
b435e9f
 
 
 
 
 
 
199996f
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
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
---
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_keras_callback
model-index:
- name: edyfjm07/distilbert-base-uncased-QA1-finetuned-squad-es
  results: []
language:
- es
metrics:
- rouge
- f1
datasets:
- edyfjm07/squad_indicaciones_es
pipeline_tag: question-answering
---

<!-- This model card has been generated automatically according to the information Keras had access to. You should
probably proofread and complete it, then remove this comment. -->

# edyfjm07/distilbert-base-uncased-QA1-finetuned-squad-es

This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Train Loss: 0.2131
- Train End Logits Accuracy: 0.9224
- Train Start Logits Accuracy: 0.9310
- Validation Loss: 1.0588
- Validation End Logits Accuracy: 0.8088
- Validation Start Logits Accuracy: 0.8150
- Epoch: 50

## 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:
- optimizer: {'name': 'Adam', 'weight_decay': None, 'clipnorm': None, 'global_clipnorm': None, 'clipvalue': None, 'use_ema': False, 'ema_momentum': 0.99, 'ema_overwrite_frequency': None, 'jit_compile': True, 'is_legacy_optimizer': False, 'learning_rate': {'module': 'keras.optimizers.schedules', 'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 1e-05, 'decay_steps': 1479, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, 'registered_name': None}, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False}
- training_precision: float32

### Training results

| Train Loss | Train End Logits Accuracy | Train Start Logits Accuracy | Validation Loss | Validation End Logits Accuracy | Validation Start Logits Accuracy | Epoch |
|:----------:|:-------------------------:|:---------------------------:|:---------------:|:------------------------------:|:--------------------------------:|:-----:|
| 5.1787     | 0.0571                    | 0.0496                      | 4.3181          | 0.1724                         | 0.1818                           | 0     |
| 3.6307     | 0.25                      | 0.1810                      | 2.8944          | 0.3793                         | 0.2476                           | 1     |
| 2.5094     | 0.3998                    | 0.3147                      | 2.1436          | 0.4514                         | 0.3793                           | 2     |
| 1.9078     | 0.4871                    | 0.4397                      | 1.7322          | 0.5204                         | 0.5705                           | 3     |
| 1.5135     | 0.5593                    | 0.5700                      | 1.4332          | 0.6050                         | 0.6238                           | 4     |
| 1.2802     | 0.5927                    | 0.6013                      | 1.3274          | 0.6270                         | 0.6364                           | 5     |
| 1.1079     | 0.6595                    | 0.6455                      | 1.2126          | 0.6520                         | 0.6865                           | 6     |
| 0.9827     | 0.6843                    | 0.7069                      | 1.1469          | 0.7116                         | 0.7116                           | 7     |
| 0.8810     | 0.7306                    | 0.7371                      | 1.0859          | 0.7116                         | 0.7053                           | 8     |
| 0.8194     | 0.7349                    | 0.7446                      | 1.0339          | 0.7429                         | 0.7492                           | 9     |
| 0.7245     | 0.7403                    | 0.7877                      | 1.0371          | 0.7304                         | 0.7398                           | 10    |
| 0.6827     | 0.7683                    | 0.7856                      | 1.0185          | 0.7492                         | 0.7461                           | 11    |
| 0.6421     | 0.7866                    | 0.8071                      | 1.0298          | 0.7492                         | 0.7555                           | 12    |
| 0.5949     | 0.8006                    | 0.8050                      | 0.9877          | 0.7586                         | 0.7774                           | 13    |
| 0.5471     | 0.8125                    | 0.8244                      | 0.9933          | 0.7398                         | 0.7774                           | 14    |
| 0.5119     | 0.8233                    | 0.8362                      | 0.9956          | 0.7524                         | 0.7837                           | 15    |
| 0.4916     | 0.8330                    | 0.8599                      | 0.9917          | 0.7398                         | 0.8025                           | 16    |
| 0.4521     | 0.8373                    | 0.8836                      | 0.9698          | 0.7680                         | 0.7868                           | 17    |
| 0.4424     | 0.8459                    | 0.8696                      | 0.9951          | 0.7712                         | 0.8025                           | 18    |
| 0.3928     | 0.8599                    | 0.8966                      | 1.0173          | 0.7618                         | 0.7931                           | 19    |
| 0.3874     | 0.8578                    | 0.8922                      | 1.0307          | 0.7649                         | 0.7931                           | 20    |
| 0.3822     | 0.8588                    | 0.8901                      | 1.0272          | 0.7680                         | 0.7900                           | 21    |
| 0.3859     | 0.8524                    | 0.8879                      | 1.0180          | 0.7555                         | 0.7962                           | 22    |
| 0.3672     | 0.8524                    | 0.8836                      | 1.0040          | 0.7837                         | 0.7994                           | 23    |
| 0.3409     | 0.8675                    | 0.8825                      | 1.0242          | 0.7900                         | 0.8088                           | 24    |
| 0.3564     | 0.8610                    | 0.8869                      | 1.0257          | 0.7900                         | 0.7900                           | 25    |
| 0.3324     | 0.8578                    | 0.9041                      | 1.0227          | 0.7837                         | 0.8088                           | 26    |
| 0.3066     | 0.8858                    | 0.9159                      | 1.0243          | 0.7900                         | 0.8025                           | 27    |
| 0.3026     | 0.8804                    | 0.9084                      | 1.0224          | 0.7774                         | 0.8088                           | 28    |
| 0.2896     | 0.8879                    | 0.9009                      | 1.0324          | 0.7649                         | 0.8182                           | 29    |
| 0.2710     | 0.8998                    | 0.9106                      | 1.0458          | 0.7868                         | 0.8088                           | 30    |
| 0.2727     | 0.8933                    | 0.9213                      | 1.0483          | 0.7806                         | 0.7931                           | 31    |
| 0.2728     | 0.8976                    | 0.9062                      | 1.0459          | 0.7868                         | 0.8088                           | 32    |
| 0.2780     | 0.8847                    | 0.9073                      | 1.0595          | 0.7962                         | 0.8056                           | 33    |
| 0.2641     | 0.8955                    | 0.9138                      | 1.0503          | 0.7868                         | 0.8025                           | 34    |
| 0.2611     | 0.9009                    | 0.9203                      | 1.0458          | 0.8025                         | 0.7962                           | 35    |
| 0.2502     | 0.9030                    | 0.9203                      | 1.0621          | 0.8025                         | 0.8025                           | 36    |
| 0.2655     | 0.8804                    | 0.9213                      | 1.0478          | 0.7994                         | 0.7994                           | 37    |
| 0.2434     | 0.9084                    | 0.9181                      | 1.0491          | 0.8025                         | 0.7994                           | 38    |
| 0.2409     | 0.9149                    | 0.9224                      | 1.0452          | 0.8025                         | 0.8088                           | 39    |
| 0.2271     | 0.9181                    | 0.9246                      | 1.0487          | 0.7962                         | 0.8119                           | 40    |
| 0.2288     | 0.9332                    | 0.9149                      | 1.0579          | 0.8056                         | 0.8056                           | 41    |
| 0.2444     | 0.9127                    | 0.9127                      | 1.0522          | 0.8056                         | 0.8119                           | 42    |
| 0.2145     | 0.9235                    | 0.9300                      | 1.0584          | 0.8025                         | 0.8088                           | 43    |
| 0.2264     | 0.9073                    | 0.9289                      | 1.0520          | 0.8025                         | 0.8119                           | 44    |
| 0.2120     | 0.9213                    | 0.9429                      | 1.0591          | 0.8119                         | 0.8088                           | 45    |
| 0.2280     | 0.9127                    | 0.9235                      | 1.0538          | 0.8088                         | 0.8056                           | 46    |
| 0.2166     | 0.9116                    | 0.9203                      | 1.0554          | 0.8088                         | 0.8088                           | 47    |
| 0.2184     | 0.9138                    | 0.9397                      | 1.0568          | 0.8119                         | 0.8088                           | 48    |
| 0.2087     | 0.9106                    | 0.9375                      | 1.0588          | 0.8088                         | 0.8150                           | 49    |
| 0.2131     | 0.9224                    | 0.9310                      | 1.0588          | 0.8088                         | 0.8150                           | 50    |


### Framework versions

- Transformers 4.41.2
- TensorFlow 2.15.0
- Datasets 2.20.0
- Tokenizers 0.19.1