Hugging Face's logo

jvalline
/
randomization_model

Transformers
PyTorch
TensorBoard
Safetensors
t5
text2text-generation
Generated from Trainer
text-generation-inference
Model card Files
xet
 Metrics Community
jvalline commited on
Commit
2be0fc4
·
verified ·
1 Parent(s): 1e2ee27

Model save

Browse files
Files changed (2) hide show
  1. README.md +43 -13
  2. generation_config.json +1 -1
README.md CHANGED
@@ -18,10 +18,10 @@ should probably proofread and complete it, then remove this comment. -->
18
 
19
  This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on the None dataset.
20
  It achieves the following results on the evaluation set:
21
- - Loss: 1.9445
22
- - Bleu: 0.0
23
  - Accuracy: 0.0
24
- - Gen Len: 18.9976
25
 
26
  ## Model description
27
 
@@ -41,23 +41,53 @@ More information needed
41
 
42
  The following hyperparameters were used during training:
43
  - learning_rate: 2e-05
44
- - train_batch_size: 8
45
- - eval_batch_size: 8
46
  - seed: 42
47
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
48
  - lr_scheduler_type: linear
49
- - num_epochs: 1
 
50
 
51
  ### Training results
52
 
53
- | Training Loss | Epoch | Step | Validation Loss | Bleu | Accuracy | Gen Len |
54
- |:-------------:|:-----:|:----:|:---------------:|:----:|:--------:|:-------:|
55
- | 2.4068 | 1.0 | 6250 | 1.9445 | 0.0 | 0.0 | 18.9976 |
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
56
 
57
 
58
  ### Framework versions
59
 
60
- - Transformers 4.32.1
61
- - Pytorch 2.3.0.dev20240113
62
- - Datasets 2.12.0
63
- - Tokenizers 0.13.2
 
18
 
19
  This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on the None dataset.
20
  It achieves the following results on the evaluation set:
21
+ - Loss: 2.2626
22
+ - Bleu: 0.0001
23
  - Accuracy: 0.0
24
+ - Gen Len: 18.999
25
 
26
  ## Model description
27
 
 
41
 
42
  The following hyperparameters were used during training:
43
  - learning_rate: 2e-05
44
+ - train_batch_size: 10
45
+ - eval_batch_size: 10
46
  - seed: 42
47
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
48
  - lr_scheduler_type: linear
49
+ - num_epochs: 3
50
+ - mixed_precision_training: Native AMP
51
 
52
  ### Training results
53
 
54
+ | Training Loss | Epoch | Step | Validation Loss | Bleu | Accuracy | Gen Len |
55
+ |:-------------:|:-----:|:----:|:---------------:|:------:|:--------:|:-------:|
56
+ | 3.0103 | 0.1 | 50 | 2.5132 | 0.0 | 0.0 | 18.9985 |
57
+ | 2.999 | 0.2 | 100 | 2.4883 | 0.0 | 0.0 | 19.0 |
58
+ | 2.9457 | 0.3 | 150 | 2.4640 | 0.0 | 0.0 | 19.0 |
59
+ | 2.8865 | 0.4 | 200 | 2.4431 | 0.0 | 0.0 | 19.0 |
60
+ | 2.8935 | 0.5 | 250 | 2.4240 | 0.0 | 0.0 | 19.0 |
61
+ | 2.8983 | 0.6 | 300 | 2.4079 | 0.0 | 0.0 | 19.0 |
62
+ | 2.8579 | 0.7 | 350 | 2.3933 | 0.0 | 0.0 | 19.0 |
63
+ | 2.8501 | 0.8 | 400 | 2.3794 | 0.0 | 0.0 | 19.0 |
64
+ | 2.7892 | 0.9 | 450 | 2.3683 | 0.0 | 0.0 | 19.0 |
65
+ | 2.7962 | 1.0 | 500 | 2.3561 | 0.0 | 0.0 | 19.0 |
66
+ | 2.8408 | 1.1 | 550 | 2.3456 | 0.0 | 0.0 | 19.0 |
67
+ | 2.8049 | 1.2 | 600 | 2.3350 | 0.0001 | 0.0 | 19.0 |
68
+ | 2.8051 | 1.3 | 650 | 2.3278 | 0.0001 | 0.0 | 19.0 |
69
+ | 2.8126 | 1.4 | 700 | 2.3192 | 0.0001 | 0.0 | 19.0 |
70
+ | 2.7689 | 1.5 | 750 | 2.3121 | 0.0001 | 0.0 | 19.0 |
71
+ | 2.7559 | 1.6 | 800 | 2.3051 | 0.0001 | 0.0 | 18.9995 |
72
+ | 2.7672 | 1.7 | 850 | 2.2978 | 0.0001 | 0.0 | 18.9985 |
73
+ | 2.7901 | 1.8 | 900 | 2.2916 | 0.0001 | 0.0 | 18.9995 |
74
+ | 2.7571 | 1.9 | 950 | 2.2868 | 0.0001 | 0.0 | 18.9985 |
75
+ | 2.7796 | 2.0 | 1000 | 2.2834 | 0.0001 | 0.0 | 18.9985 |
76
+ | 2.7393 | 2.1 | 1050 | 2.2798 | 0.0001 | 0.0 | 18.9985 |
77
+ | 2.7309 | 2.2 | 1100 | 2.2757 | 0.0001 | 0.0 | 18.9985 |
78
+ | 2.7703 | 2.3 | 1150 | 2.2729 | 0.0001 | 0.0 | 18.999 |
79
+ | 2.7354 | 2.4 | 1200 | 2.2703 | 0.0001 | 0.0 | 18.999 |
80
+ | 2.7428 | 2.5 | 1250 | 2.2678 | 0.0001 | 0.0 | 18.999 |
81
+ | 2.7571 | 2.6 | 1300 | 2.2661 | 0.0001 | 0.0 | 18.999 |
82
+ | 2.7218 | 2.7 | 1350 | 2.2645 | 0.0001 | 0.0 | 18.999 |
83
+ | 2.7051 | 2.8 | 1400 | 2.2634 | 0.0001 | 0.0 | 18.999 |
84
+ | 2.7466 | 2.9 | 1450 | 2.2628 | 0.0001 | 0.0 | 18.999 |
85
+ | 2.722 | 3.0 | 1500 | 2.2626 | 0.0001 | 0.0 | 18.999 |
86
 
87
 
88
  ### Framework versions
89
 
90
+ - Transformers 4.37.1
91
+ - Pytorch 2.1.0+cu121
92
+ - Datasets 2.16.1
93
+ - Tokenizers 0.15.1
generation_config.json CHANGED
@@ -2,5 +2,5 @@
2
  "decoder_start_token_id": 0,
3
  "eos_token_id": 1,
4
  "pad_token_id": 0,
5
- "transformers_version": "4.32.1"
6
  }
 
2
  "decoder_start_token_id": 0,
3
  "eos_token_id": 1,
4
  "pad_token_id": 0,
5
+ "transformers_version": "4.37.1"
6
  }