Hugging Face's logo

mtzig
/
lge_tests_prelim

Transformers
Safetensors
nanogpt
Generated from Trainer
Inference Endpoints
Model card Files Community
mtzig commited on
Commit
c3b3275
·
verified ·
1 Parent(s): 78572cf

Model save

Browse files
Files changed (4) hide show
  1. README.md +80 -80
  2. config.json +3 -3
  3. model.safetensors +2 -2
  4. training_args.bin +1 -1
README.md CHANGED
@@ -16,7 +16,7 @@ should probably proofread and complete it, then remove this comment. -->
16
 
17
  This model is a fine-tuned version of [](https://huggingface.co/) on an unknown dataset.
18
  It achieves the following results on the evaluation set:
19
- - Loss: 1.9351
20
  - Accuracy: 0.0
21
 
22
  ## Model description
@@ -49,85 +49,85 @@ The following hyperparameters were used during training:
49
 
50
  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
51
  |:-------------:|:------:|:----:|:---------------:|:--------:|
52
- | No log | 0 | 0 | 2.6352 | 0.0 |
53
- | 2.6162 | 0.0128 | 100 | 2.6142 | 0.0 |
54
- | 2.5762 | 0.0256 | 200 | 2.5696 | 0.0 |
55
- | 2.5183 | 0.0384 | 300 | 2.5098 | 0.0 |
56
- | 2.4384 | 0.0512 | 400 | 2.4388 | 0.0 |
57
- | 2.3826 | 0.0640 | 500 | 2.3823 | 0.0 |
58
- | 2.3524 | 0.0768 | 600 | 2.3453 | 0.0 |
59
- | 2.2912 | 0.0896 | 700 | 2.2903 | 0.0 |
60
- | 2.2263 | 0.1024 | 800 | 2.2430 | 0.0 |
61
- | 2.1825 | 0.1152 | 900 | 2.1660 | 0.0 |
62
- | 2.1277 | 0.1280 | 1000 | 2.1219 | 0.0 |
63
- | 2.0904 | 0.1408 | 1100 | 2.0796 | 0.0 |
64
- | 2.076 | 0.1536 | 1200 | 2.0615 | 0.0 |
65
- | 2.021 | 0.1665 | 1300 | 2.0367 | 0.0 |
66
- | 2.0195 | 0.1793 | 1400 | 2.0154 | 0.0 |
67
- | 2.0071 | 0.1921 | 1500 | 2.0006 | 0.0 |
68
- | 2.0183 | 0.2049 | 1600 | 2.0048 | 0.0 |
69
- | 1.9959 | 0.2177 | 1700 | 1.9942 | 0.0 |
70
- | 2.006 | 0.2305 | 1800 | 1.9842 | 0.0 |
71
- | 2.036 | 0.2433 | 1900 | 2.0020 | 0.0 |
72
- | 2.0021 | 0.2561 | 2000 | 1.9790 | 0.0 |
73
- | 1.993 | 0.2689 | 2100 | 1.9718 | 0.0 |
74
- | 1.9941 | 0.2817 | 2200 | 1.9788 | 0.0 |
75
- | 1.9822 | 0.2945 | 2300 | 1.9824 | 0.0 |
76
- | 1.9802 | 0.3073 | 2400 | 1.9661 | 0.0 |
77
- | 1.9943 | 0.3201 | 2500 | 1.9715 | 0.0 |
78
- | 1.9685 | 0.3329 | 2600 | 1.9719 | 0.0 |
79
- | 1.9835 | 0.3457 | 2700 | 1.9665 | 0.0 |
80
- | 1.9886 | 0.3585 | 2800 | 1.9619 | 0.0 |
81
- | 1.9732 | 0.3713 | 2900 | 1.9605 | 0.0 |
82
- | 1.9818 | 0.3841 | 3000 | 1.9612 | 0.0 |
83
- | 1.9983 | 0.3969 | 3100 | 1.9617 | 0.0 |
84
- | 1.9942 | 0.4097 | 3200 | 1.9590 | 0.0 |
85
- | 1.9787 | 0.4225 | 3300 | 1.9588 | 0.0 |
86
- | 2.0028 | 0.4353 | 3400 | 1.9624 | 0.0 |
87
- | 1.9867 | 0.4481 | 3500 | 1.9643 | 0.0 |
88
- | 1.9798 | 0.4609 | 3600 | 2.0142 | 0.0 |
89
- | 1.9831 | 0.4738 | 3700 | 1.9564 | 0.0 |
90
- | 1.9829 | 0.4866 | 3800 | 1.9550 | 0.0 |
91
- | 1.9889 | 0.4994 | 3900 | 1.9585 | 0.0 |
92
- | 1.9712 | 0.5122 | 4000 | 1.9576 | 0.0 |
93
- | 1.9995 | 0.5250 | 4100 | 1.9568 | 0.0 |
94
- | 1.9394 | 0.5378 | 4200 | 1.9535 | 0.0 |
95
- | 1.9688 | 0.5506 | 4300 | 1.9519 | 0.0 |
96
- | 1.9853 | 0.5634 | 4400 | 1.9543 | 0.0 |
97
- | 1.9707 | 0.5762 | 4500 | 1.9536 | 0.0 |
98
- | 1.9818 | 0.5890 | 4600 | 1.9521 | 0.0 |
99
- | 1.9847 | 0.6018 | 4700 | 1.9534 | 0.0 |
100
- | 1.9573 | 0.6146 | 4800 | 1.9546 | 0.0 |
101
- | 1.9682 | 0.6274 | 4900 | 1.9487 | 0.0 |
102
- | 1.9636 | 0.6402 | 5000 | 1.9520 | 0.0 |
103
- | 1.9405 | 0.6530 | 5100 | 1.9493 | 0.0 |
104
- | 2.0023 | 0.6658 | 5200 | 1.9600 | 0.0 |
105
- | 1.9715 | 0.6786 | 5300 | 1.9516 | 0.0 |
106
- | 1.9668 | 0.6914 | 5400 | 1.9486 | 0.0 |
107
- | 1.9549 | 0.7042 | 5500 | 1.9509 | 0.0 |
108
- | 1.9408 | 0.7170 | 5600 | 1.9471 | 0.0 |
109
- | 1.9532 | 0.7298 | 5700 | 1.9619 | 0.0 |
110
- | 1.9705 | 0.7426 | 5800 | 1.9444 | 0.0 |
111
- | 1.9729 | 0.7554 | 5900 | 1.9410 | 0.0 |
112
- | 1.9462 | 0.7682 | 6000 | 1.9470 | 0.0 |
113
- | 1.9871 | 0.7810 | 6100 | 1.9456 | 0.0 |
114
- | 1.9634 | 0.7939 | 6200 | 1.9381 | 0.0 |
115
- | 1.9754 | 0.8067 | 6300 | 1.9432 | 0.0 |
116
- | 1.9248 | 0.8195 | 6400 | 1.9373 | 0.0 |
117
- | 1.9394 | 0.8323 | 6500 | 1.9398 | 0.0 |
118
- | 1.9486 | 0.8451 | 6600 | 1.9422 | 0.0 |
119
- | 1.9427 | 0.8579 | 6700 | 1.9385 | 0.0 |
120
- | 1.9551 | 0.8707 | 6800 | 1.9374 | 0.0 |
121
- | 1.9567 | 0.8835 | 6900 | 1.9360 | 0.0 |
122
- | 1.9824 | 0.8963 | 7000 | 1.9361 | 0.0 |
123
- | 1.9895 | 0.9091 | 7100 | 1.9366 | 0.0 |
124
- | 1.9713 | 0.9219 | 7200 | 1.9361 | 0.0 |
125
- | 1.9856 | 0.9347 | 7300 | 1.9368 | 0.0 |
126
- | 1.9638 | 0.9475 | 7400 | 1.9355 | 0.0 |
127
- | 1.9632 | 0.9603 | 7500 | 1.9350 | 0.0 |
128
- | 1.9693 | 0.9731 | 7600 | 1.9351 | 0.0 |
129
- | 1.9666 | 0.9859 | 7700 | 1.9351 | 0.0 |
130
- | 1.9529 | 0.9987 | 7800 | 1.9351 | 0.0 |
131
 
132
 
133
  ### Framework versions
 
16
 
17
  This model is a fine-tuned version of [](https://huggingface.co/) on an unknown dataset.
18
  It achieves the following results on the evaluation set:
19
+ - Loss: 1.6817
20
  - Accuracy: 0.0
21
 
22
  ## Model description
 
49
 
50
  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
51
  |:-------------:|:------:|:----:|:---------------:|:--------:|
52
+ | No log | 0 | 0 | 2.6804 | 0.0 |
53
+ | 2.2675 | 0.0128 | 100 | 2.2266 | 0.0 |
54
+ | 2.1492 | 0.0256 | 200 | 2.1178 | 0.0 |
55
+ | 2.1295 | 0.0384 | 300 | 2.0687 | 0.0 |
56
+ | 2.2024 | 0.0512 | 400 | 2.1664 | 0.0 |
57
+ | 2.0 | 0.0640 | 500 | 1.9627 | 0.0 |
58
+ | 2.0962 | 0.0768 | 600 | 2.1138 | 0.0 |
59
+ | 2.0072 | 0.0896 | 700 | 2.0115 | 0.0 |
60
+ | 2.097 | 0.1024 | 800 | 2.0415 | 0.0 |
61
+ | 2.0797 | 0.1152 | 900 | 1.9546 | 0.0 |
62
+ | 1.9762 | 0.1280 | 1000 | 2.1161 | 0.0 |
63
+ | 1.9884 | 0.1408 | 1100 | 1.9407 | 0.0 |
64
+ | 1.9643 | 0.1536 | 1200 | 1.9384 | 0.0 |
65
+ | 1.9923 | 0.1665 | 1300 | 1.9917 | 0.0 |
66
+ | 1.947 | 0.1793 | 1400 | 1.9375 | 0.0 |
67
+ | 1.9744 | 0.1921 | 1500 | 1.9428 | 0.0 |
68
+ | 1.9553 | 0.2049 | 1600 | 1.9343 | 0.0 |
69
+ | 1.9432 | 0.2177 | 1700 | 1.9203 | 0.0 |
70
+ | 1.9371 | 0.2305 | 1800 | 1.9146 | 0.0 |
71
+ | 1.9352 | 0.2433 | 1900 | 1.9568 | 0.0 |
72
+ | 1.9524 | 0.2561 | 2000 | 1.9041 | 0.0 |
73
+ | 1.9202 | 0.2689 | 2100 | 1.8986 | 0.0 |
74
+ | 1.9001 | 0.2817 | 2200 | 1.8738 | 0.0 |
75
+ | 1.9562 | 0.2945 | 2300 | 1.9206 | 0.0 |
76
+ | 1.8877 | 0.3073 | 2400 | 1.9163 | 0.0 |
77
+ | 1.8626 | 0.3201 | 2500 | 1.8233 | 0.0 |
78
+ | 1.8348 | 0.3329 | 2600 | 1.8809 | 0.0 |
79
+ | 1.8347 | 0.3457 | 2700 | 1.8131 | 0.0 |
80
+ | 1.8213 | 0.3585 | 2800 | 1.7922 | 0.0 |
81
+ | 1.7962 | 0.3713 | 2900 | 1.8129 | 0.0 |
82
+ | 1.8744 | 0.3841 | 3000 | 1.8993 | 0.0 |
83
+ | 1.8734 | 0.3969 | 3100 | 1.8109 | 0.0 |
84
+ | 1.9698 | 0.4097 | 3200 | 1.8633 | 0.0 |
85
+ | 1.9312 | 0.4225 | 3300 | 1.8544 | 0.0 |
86
+ | 1.8277 | 0.4353 | 3400 | 1.7484 | 0.0 |
87
+ | 1.7854 | 0.4481 | 3500 | 1.7561 | 0.0 |
88
+ | 1.7452 | 0.4609 | 3600 | 1.7582 | 0.0 |
89
+ | 1.802 | 0.4738 | 3700 | 1.7538 | 0.0 |
90
+ | 1.7698 | 0.4866 | 3800 | 1.7321 | 0.0 |
91
+ | 1.7697 | 0.4994 | 3900 | 1.7262 | 0.0 |
92
+ | 1.7468 | 0.5122 | 4000 | 1.7293 | 0.0 |
93
+ | 1.7811 | 0.5250 | 4100 | 1.7334 | 0.0 |
94
+ | 1.7113 | 0.5378 | 4200 | 1.7089 | 0.0 |
95
+ | 1.7738 | 0.5506 | 4300 | 1.7482 | 0.0 |
96
+ | 1.7791 | 0.5634 | 4400 | 1.7244 | 0.0 |
97
+ | 1.742 | 0.5762 | 4500 | 1.7046 | 0.0 |
98
+ | 1.7209 | 0.5890 | 4600 | 1.6993 | 0.0 |
99
+ | 1.7457 | 0.6018 | 4700 | 1.7321 | 0.0 |
100
+ | 1.7085 | 0.6146 | 4800 | 1.6991 | 0.0 |
101
+ | 1.718 | 0.6274 | 4900 | 1.6914 | 0.0 |
102
+ | 1.7197 | 0.6402 | 5000 | 1.6944 | 0.0 |
103
+ | 1.6825 | 0.6530 | 5100 | 1.6938 | 0.0 |
104
+ | 1.7476 | 0.6658 | 5200 | 1.6952 | 0.0 |
105
+ | 1.7131 | 0.6786 | 5300 | 1.6917 | 0.0 |
106
+ | 1.8437 | 0.6914 | 5400 | 1.8308 | 0.0 |
107
+ | 1.7133 | 0.7042 | 5500 | 1.6897 | 0.0 |
108
+ | 1.6871 | 0.7170 | 5600 | 1.6904 | 0.0 |
109
+ | 1.7024 | 0.7298 | 5700 | 1.6852 | 0.0 |
110
+ | 1.7467 | 0.7426 | 5800 | 1.6853 | 0.0 |
111
+ | 1.7108 | 0.7554 | 5900 | 1.6861 | 0.0 |
112
+ | 1.6875 | 0.7682 | 6000 | 1.6835 | 0.0 |
113
+ | 1.7171 | 0.7810 | 6100 | 1.6823 | 0.0 |
114
+ | 1.7107 | 0.7939 | 6200 | 1.6817 | 0.0 |
115
+ | 1.7082 | 0.8067 | 6300 | 1.6833 | 0.0 |
116
+ | 1.6806 | 0.8195 | 6400 | 1.6833 | 0.0 |
117
+ | 1.6861 | 0.8323 | 6500 | 1.6829 | 0.0 |
118
+ | 1.6941 | 0.8451 | 6600 | 1.6819 | 0.0 |
119
+ | 1.6907 | 0.8579 | 6700 | 1.6823 | 0.0 |
120
+ | 1.7049 | 0.8707 | 6800 | 1.6810 | 0.0 |
121
+ | 1.6958 | 0.8835 | 6900 | 1.6816 | 0.0 |
122
+ | 1.7268 | 0.8963 | 7000 | 1.6817 | 0.0 |
123
+ | 1.7255 | 0.9091 | 7100 | 1.6822 | 0.0 |
124
+ | 1.7086 | 0.9219 | 7200 | 1.6820 | 0.0 |
125
+ | 1.7244 | 0.9347 | 7300 | 1.6819 | 0.0 |
126
+ | 1.6964 | 0.9475 | 7400 | 1.6822 | 0.0 |
127
+ | 1.7062 | 0.9603 | 7500 | 1.6817 | 0.0 |
128
+ | 1.7114 | 0.9731 | 7600 | 1.6817 | 0.0 |
129
+ | 1.7363 | 0.9859 | 7700 | 1.6817 | 0.0 |
130
+ | 1.7008 | 0.9987 | 7800 | 1.6817 | 0.0 |
131
 
132
 
133
  ### Framework versions
config.json CHANGED
@@ -6,9 +6,9 @@
6
  "block_size": 1024,
7
  "dropout": 0.0,
8
  "model_type": "nanogpt",
9
- "n_embd": 5,
10
- "n_head": 1,
11
- "n_layer": 2,
12
  "nonlinearity": "RELU",
13
  "torch_dtype": "float32",
14
  "transformers_version": "4.46.0",
 
6
  "block_size": 1024,
7
  "dropout": 0.0,
8
  "model_type": "nanogpt",
9
+ "n_embd": 256,
10
+ "n_head": 4,
11
+ "n_layer": 6,
12
  "nonlinearity": "RELU",
13
  "torch_dtype": "float32",
14
  "transformers_version": "4.46.0",
model.safetensors CHANGED
@@ -1,3 +1,3 @@
1
  version https://git-lfs.github.com/spec/v1
2
- oid sha256:059434991b15e530bb061c3a2ab34453fdea8814a3121b809a0a14ba1b05ae1b
3
- size 6000
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:6cd20fe4264a048350bfce60a3ffe0e233953a037b9f69d12fbce8e9e1e35fb5
3
+ size 18992440
training_args.bin CHANGED
@@ -1,3 +1,3 @@
1
  version https://git-lfs.github.com/spec/v1
2
- oid sha256:fb3d894cf2cd045c36b2c6a765b5353f7f3c9c0cd22df070af4e058ac35d61f7
3
  size 5240
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:e8035e194bf556bda66bfb9185a91338ab3f8fbfd93089290724b06b5a981518
3
  size 5240