Hugging Face's logo

mtzig
/
maze_lr5e-4_batch128_trainn30h1-9_evaltrain10

Transformers
Safetensors
nanogpt
Generated from Trainer
Model card Files
xet
Community
mtzig commited on
Commit
04bd004
·
verified ·
1 Parent(s): ecb19ac

Model save

Browse files
Files changed (5) hide show
  1. README.md +294 -0
  2. config.json +19 -0
  3. generation_config.json +4 -0
  4. model.safetensors +3 -0
  5. training_args.bin +3 -0
README.md ADDED
@@ -0,0 +1,294 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ library_name: transformers
3
+ tags:
4
+ - generated_from_trainer
5
+ metrics:
6
+ - accuracy
7
+ model-index:
8
+ - name: maze_lr5e-4_batch128_trainn30h1-9_evaltrain10
9
+ results: []
10
+ ---
11
+
12
+ <!-- This model card has been generated automatically according to the information the Trainer had access to. You
13
+ should probably proofread and complete it, then remove this comment. -->
14
+
15
+ # maze_lr5e-4_batch128_trainn30h1-9_evaltrain10
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: 1.4211
20
+ - Accuracy: 0.0
21
+
22
+ ## Model description
23
+
24
+ More information needed
25
+
26
+ ## Intended uses & limitations
27
+
28
+ More information needed
29
+
30
+ ## Training and evaluation data
31
+
32
+ More information needed
33
+
34
+ ## Training procedure
35
+
36
+ ### Training hyperparameters
37
+
38
+ The following hyperparameters were used during training:
39
+ - learning_rate: 0.0005
40
+ - train_batch_size: 128
41
+ - eval_batch_size: 128
42
+ - seed: 23452399
43
+ - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
44
+ - lr_scheduler_type: cosine
45
+ - lr_scheduler_warmup_ratio: 0.1
46
+ - num_epochs: 1
47
+
48
+ ### Training results
49
+
50
+ | Training Loss | Epoch | Step | Validation Loss | Accuracy |
51
+ |:-------------:|:------:|:-----:|:---------------:|:--------:|
52
+ | No log | 0 | 0 | 4.9472 | 0.0 |
53
+ | 2.5273 | 0.0043 | 100 | 2.4811 | 0.0 |
54
+ | 2.0076 | 0.0085 | 200 | 2.1404 | 0.0 |
55
+ | 1.833 | 0.0128 | 300 | 2.0255 | 0.0 |
56
+ | 1.7784 | 0.0171 | 400 | 1.9689 | 0.0 |
57
+ | 1.6032 | 0.0213 | 500 | 1.9130 | 0.0 |
58
+ | 1.4937 | 0.0256 | 600 | 1.7262 | 0.0 |
59
+ | 1.4136 | 0.0299 | 700 | 1.6964 | 0.0 |
60
+ | 1.4272 | 0.0341 | 800 | 1.6855 | 0.0 |
61
+ | 1.412 | 0.0384 | 900 | 1.6789 | 0.0 |
62
+ | 1.3859 | 0.0427 | 1000 | 1.6599 | 0.0 |
63
+ | 1.3495 | 0.0469 | 1100 | 1.6401 | 0.0 |
64
+ | 1.326 | 0.0512 | 1200 | 1.6323 | 0.0 |
65
+ | 1.3777 | 0.0555 | 1300 | 1.6145 | 0.0 |
66
+ | 1.3538 | 0.0597 | 1400 | 1.6118 | 0.0 |
67
+ | 1.3664 | 0.0640 | 1500 | 1.6173 | 0.0 |
68
+ | 1.3698 | 0.0683 | 1600 | 1.6136 | 0.0 |
69
+ | 1.3216 | 0.0725 | 1700 | 1.5971 | 0.0 |
70
+ | 1.3741 | 0.0768 | 1800 | 1.6026 | 0.0 |
71
+ | 1.3111 | 0.0811 | 1900 | 1.5885 | 0.0 |
72
+ | 1.3019 | 0.0853 | 2000 | 1.5837 | 0.0 |
73
+ | 1.3365 | 0.0896 | 2100 | 1.5684 | 0.0 |
74
+ | 1.296 | 0.0939 | 2200 | 1.5814 | 0.0 |
75
+ | 1.3121 | 0.0981 | 2300 | 1.5422 | 0.0 |
76
+ | 1.2279 | 0.1024 | 2400 | 1.5707 | 0.0 |
77
+ | 1.2968 | 0.1067 | 2500 | 1.5314 | 0.0 |
78
+ | 1.2821 | 0.1109 | 2600 | 1.5905 | 0.0 |
79
+ | 1.2496 | 0.1152 | 2700 | 1.6026 | 0.0 |
80
+ | 1.1901 | 0.1195 | 2800 | 1.5776 | 0.0 |
81
+ | 1.2522 | 0.1237 | 2900 | 1.5011 | 0.0 |
82
+ | 1.2686 | 0.1280 | 3000 | 1.6446 | 0.0 |
83
+ | 1.2461 | 0.1323 | 3100 | 1.5346 | 0.0 |
84
+ | 1.2305 | 0.1365 | 3200 | 1.4999 | 0.0 |
85
+ | 1.2056 | 0.1408 | 3300 | 1.5216 | 0.0 |
86
+ | 1.2148 | 0.1451 | 3400 | 1.4988 | 0.0 |
87
+ | 1.2422 | 0.1493 | 3500 | 1.4826 | 0.0 |
88
+ | 1.1714 | 0.1536 | 3600 | 1.5429 | 0.0 |
89
+ | 1.2175 | 0.1579 | 3700 | 1.4911 | 0.0 |
90
+ | 1.2069 | 0.1621 | 3800 | 1.5228 | 0.0 |
91
+ | 1.2051 | 0.1664 | 3900 | 1.4570 | 0.0 |
92
+ | 1.2236 | 0.1707 | 4000 | 1.5215 | 0.0 |
93
+ | 1.1935 | 0.1749 | 4100 | 1.4656 | 0.0 |
94
+ | 1.1658 | 0.1792 | 4200 | 1.5137 | 0.0 |
95
+ | 1.1897 | 0.1835 | 4300 | 1.5847 | 0.0 |
96
+ | 1.2048 | 0.1877 | 4400 | 1.5681 | 0.0 |
97
+ | 1.1728 | 0.1920 | 4500 | 1.5154 | 0.0 |
98
+ | 1.1458 | 0.1963 | 4600 | 1.5202 | 0.0 |
99
+ | 1.1809 | 0.2005 | 4700 | 1.4473 | 0.0 |
100
+ | 1.1818 | 0.2048 | 4800 | 1.5478 | 0.0 |
101
+ | 1.1486 | 0.2091 | 4900 | 1.4301 | 0.0 |
102
+ | 1.1905 | 0.2133 | 5000 | 1.4952 | 0.0 |
103
+ | 1.1646 | 0.2176 | 5100 | 1.5255 | 0.0 |
104
+ | 1.1779 | 0.2219 | 5200 | 1.5157 | 0.0 |
105
+ | 1.1573 | 0.2261 | 5300 | 1.4653 | 0.0 |
106
+ | 1.1275 | 0.2304 | 5400 | 1.4517 | 0.0 |
107
+ | 1.1926 | 0.2347 | 5500 | 1.4415 | 0.0 |
108
+ | 1.1424 | 0.2389 | 5600 | 1.5124 | 0.0 |
109
+ | 1.1417 | 0.2432 | 5700 | 1.4636 | 0.0 |
110
+ | 1.16 | 0.2475 | 5800 | 1.4315 | 0.0 |
111
+ | 1.1194 | 0.2517 | 5900 | 1.4990 | 0.0 |
112
+ | 1.1848 | 0.2560 | 6000 | 1.4105 | 0.0 |
113
+ | 1.0978 | 0.2603 | 6100 | 1.4615 | 0.0 |
114
+ | 1.1023 | 0.2645 | 6200 | 1.4883 | 0.0 |
115
+ | 1.1353 | 0.2688 | 6300 | 1.4629 | 0.0 |
116
+ | 1.1092 | 0.2731 | 6400 | 1.5146 | 0.0 |
117
+ | 1.1362 | 0.2773 | 6500 | 1.4968 | 0.0 |
118
+ | 1.1204 | 0.2816 | 6600 | 1.5600 | 0.0 |
119
+ | 1.1218 | 0.2859 | 6700 | 1.4859 | 0.0 |
120
+ | 1.135 | 0.2901 | 6800 | 1.4882 | 0.0 |
121
+ | 1.1185 | 0.2944 | 6900 | 1.5991 | 0.0 |
122
+ | 1.1194 | 0.2987 | 7000 | 1.4917 | 0.0 |
123
+ | 1.0958 | 0.3029 | 7100 | 1.5406 | 0.0 |
124
+ | 1.0903 | 0.3072 | 7200 | 1.4738 | 0.0 |
125
+ | 1.131 | 0.3115 | 7300 | 1.4239 | 0.0 |
126
+ | 1.103 | 0.3157 | 7400 | 1.5771 | 0.0 |
127
+ | 1.1337 | 0.3200 | 7500 | 1.3729 | 0.0 |
128
+ | 1.1069 | 0.3243 | 7600 | 1.5087 | 0.0 |
129
+ | 1.1108 | 0.3285 | 7700 | 1.5018 | 0.0 |
130
+ | 1.077 | 0.3328 | 7800 | 1.4224 | 0.0 |
131
+ | 1.0851 | 0.3371 | 7900 | 1.4890 | 0.0 |
132
+ | 1.1019 | 0.3413 | 8000 | 1.5387 | 0.0 |
133
+ | 1.0869 | 0.3456 | 8100 | 1.5827 | 0.0 |
134
+ | 1.0502 | 0.3499 | 8200 | 1.3698 | 0.0 |
135
+ | 1.1244 | 0.3541 | 8300 | 1.5857 | 0.0 |
136
+ | 1.0878 | 0.3584 | 8400 | 1.5998 | 0.0 |
137
+ | 1.0629 | 0.3627 | 8500 | 1.4544 | 0.0 |
138
+ | 1.1106 | 0.3669 | 8600 | 1.4711 | 0.0 |
139
+ | 1.0657 | 0.3712 | 8700 | 1.5921 | 0.0 |
140
+ | 1.0665 | 0.3755 | 8800 | 1.4250 | 0.0 |
141
+ | 1.073 | 0.3797 | 8900 | 1.4432 | 0.0 |
142
+ | 1.0532 | 0.3840 | 9000 | 1.4229 | 0.0 |
143
+ | 1.0508 | 0.3883 | 9100 | 1.4380 | 0.0 |
144
+ | 1.0556 | 0.3925 | 9200 | 1.4593 | 0.0 |
145
+ | 1.0448 | 0.3968 | 9300 | 1.5220 | 0.0 |
146
+ | 1.0827 | 0.4011 | 9400 | 1.4043 | 0.0 |
147
+ | 1.0648 | 0.4053 | 9500 | 1.4087 | 0.0 |
148
+ | 1.0529 | 0.4096 | 9600 | 1.4175 | 0.0 |
149
+ | 1.031 | 0.4139 | 9700 | 1.4793 | 0.0 |
150
+ | 1.0257 | 0.4181 | 9800 | 1.6000 | 0.0 |
151
+ | 0.9942 | 0.4224 | 9900 | 1.4027 | 0.0 |
152
+ | 1.0654 | 0.4267 | 10000 | 1.5267 | 0.0 |
153
+ | 1.0075 | 0.4309 | 10100 | 1.5189 | 0.0 |
154
+ | 1.0082 | 0.4352 | 10200 | 1.5333 | 0.0 |
155
+ | 1.0348 | 0.4395 | 10300 | 1.3967 | 0.0 |
156
+ | 1.0372 | 0.4437 | 10400 | 1.4117 | 0.0 |
157
+ | 1.0667 | 0.4480 | 10500 | 1.5423 | 0.0 |
158
+ | 0.9735 | 0.4523 | 10600 | 1.4345 | 0.0 |
159
+ | 1.0014 | 0.4565 | 10700 | 1.5642 | 0.0 |
160
+ | 1.0082 | 0.4608 | 10800 | 1.3368 | 0.0 |
161
+ | 1.0184 | 0.4651 | 10900 | 1.4536 | 0.0 |
162
+ | 1.0157 | 0.4693 | 11000 | 1.4964 | 0.0 |
163
+ | 1.0454 | 0.4736 | 11100 | 1.5736 | 0.0 |
164
+ | 0.995 | 0.4779 | 11200 | 1.4325 | 0.0 |
165
+ | 0.9907 | 0.4821 | 11300 | 1.4136 | 0.0 |
166
+ | 0.9571 | 0.4864 | 11400 | 1.3558 | 0.0 |
167
+ | 0.9728 | 0.4907 | 11500 | 1.4881 | 0.0 |
168
+ | 0.9876 | 0.4949 | 11600 | 1.4850 | 0.0 |
169
+ | 0.958 | 0.4992 | 11700 | 1.5503 | 0.0 |
170
+ | 0.9798 | 0.5035 | 11800 | 1.2786 | 0.0 |
171
+ | 0.9516 | 0.5077 | 11900 | 1.4740 | 0.0 |
172
+ | 0.9573 | 0.5120 | 12000 | 1.4563 | 0.0 |
173
+ | 0.9102 | 0.5163 | 12100 | 1.4255 | 0.0 |
174
+ | 0.9749 | 0.5205 | 12200 | 1.2806 | 0.0 |
175
+ | 0.9379 | 0.5248 | 12300 | 1.4497 | 0.0 |
176
+ | 0.9294 | 0.5291 | 12400 | 1.5825 | 0.0 |
177
+ | 0.9509 | 0.5333 | 12500 | 1.4444 | 0.0 |
178
+ | 0.951 | 0.5376 | 12600 | 1.5147 | 0.0 |
179
+ | 0.9078 | 0.5419 | 12700 | 1.2847 | 0.0 |
180
+ | 0.9567 | 0.5461 | 12800 | 1.5289 | 0.0 |
181
+ | 0.9616 | 0.5504 | 12900 | 1.4827 | 0.0 |
182
+ | 0.8915 | 0.5547 | 13000 | 1.4428 | 0.0 |
183
+ | 0.939 | 0.5589 | 13100 | 1.5873 | 0.0 |
184
+ | 0.9279 | 0.5632 | 13200 | 1.5609 | 0.0 |
185
+ | 0.9068 | 0.5675 | 13300 | 1.5065 | 0.0 |
186
+ | 0.9544 | 0.5717 | 13400 | 1.4297 | 0.0 |
187
+ | 0.9164 | 0.5760 | 13500 | 1.5680 | 0.0 |
188
+ | 0.9021 | 0.5803 | 13600 | 1.5354 | 0.0 |
189
+ | 0.9234 | 0.5845 | 13700 | 1.5284 | 0.0 |
190
+ | 0.9551 | 0.5888 | 13800 | 1.4314 | 0.0 |
191
+ | 0.8959 | 0.5931 | 13900 | 1.5715 | 0.0 |
192
+ | 0.9459 | 0.5973 | 14000 | 1.3619 | 0.0 |
193
+ | 0.9067 | 0.6016 | 14100 | 1.4982 | 0.0 |
194
+ | 0.9018 | 0.6059 | 14200 | 1.6362 | 0.0 |
195
+ | 0.922 | 0.6101 | 14300 | 1.5055 | 0.0 |
196
+ | 0.9171 | 0.6144 | 14400 | 1.6095 | 0.0 |
197
+ | 0.8792 | 0.6187 | 14500 | 1.5764 | 0.0 |
198
+ | 0.865 | 0.6229 | 14600 | 1.5701 | 0.0 |
199
+ | 0.895 | 0.6272 | 14700 | 1.4485 | 0.0 |
200
+ | 0.9432 | 0.6315 | 14800 | 1.6390 | 0.0 |
201
+ | 0.8498 | 0.6357 | 14900 | 1.4791 | 0.0 |
202
+ | 0.891 | 0.6400 | 15000 | 1.4296 | 0.0 |
203
+ | 0.8491 | 0.6443 | 15100 | 1.5680 | 0.0 |
204
+ | 0.9185 | 0.6485 | 15200 | 1.4913 | 0.0 |
205
+ | 0.8904 | 0.6528 | 15300 | 1.5250 | 0.0 |
206
+ | 0.8954 | 0.6571 | 15400 | 1.5320 | 0.0 |
207
+ | 0.8422 | 0.6613 | 15500 | 1.4705 | 0.0 |
208
+ | 0.8475 | 0.6656 | 15600 | 1.5186 | 0.0 |
209
+ | 0.8841 | 0.6699 | 15700 | 1.4206 | 0.0 |
210
+ | 0.8478 | 0.6741 | 15800 | 1.4708 | 0.0 |
211
+ | 0.8499 | 0.6784 | 15900 | 1.4497 | 0.0 |
212
+ | 0.8745 | 0.6827 | 16000 | 1.5400 | 0.0 |
213
+ | 0.8304 | 0.6869 | 16100 | 1.4858 | 0.0 |
214
+ | 0.8749 | 0.6912 | 16200 | 1.5209 | 0.0 |
215
+ | 0.8009 | 0.6955 | 16300 | 1.5364 | 0.0 |
216
+ | 0.8132 | 0.6997 | 16400 | 1.6003 | 0.0 |
217
+ | 0.8257 | 0.7040 | 16500 | 1.5490 | 0.0 |
218
+ | 0.8614 | 0.7083 | 16600 | 1.4073 | 0.0 |
219
+ | 0.8463 | 0.7125 | 16700 | 1.4362 | 0.0 |
220
+ | 0.8206 | 0.7168 | 16800 | 1.5375 | 0.0 |
221
+ | 0.8458 | 0.7211 | 16900 | 1.5739 | 0.0 |
222
+ | 0.7877 | 0.7253 | 17000 | 1.5464 | 0.0 |
223
+ | 0.8605 | 0.7296 | 17100 | 1.5231 | 0.0 |
224
+ | 0.8596 | 0.7339 | 17200 | 1.4523 | 0.0 |
225
+ | 0.8381 | 0.7381 | 17300 | 1.5987 | 0.0 |
226
+ | 0.8348 | 0.7424 | 17400 | 1.5529 | 0.0 |
227
+ | 0.7792 | 0.7467 | 17500 | 1.5130 | 0.0 |
228
+ | 0.805 | 0.7509 | 17600 | 1.5810 | 0.0 |
229
+ | 0.8188 | 0.7552 | 17700 | 1.4650 | 0.0 |
230
+ | 0.7534 | 0.7595 | 17800 | 1.5000 | 0.0 |
231
+ | 0.8087 | 0.7637 | 17900 | 1.4991 | 0.0 |
232
+ | 0.8055 | 0.7680 | 18000 | 1.4940 | 0.0 |
233
+ | 0.8148 | 0.7723 | 18100 | 1.5806 | 0.0 |
234
+ | 0.8045 | 0.7765 | 18200 | 1.5566 | 0.0 |
235
+ | 0.7975 | 0.7808 | 18300 | 1.4962 | 0.0 |
236
+ | 0.8363 | 0.7850 | 18400 | 1.5107 | 0.0 |
237
+ | 0.7925 | 0.7893 | 18500 | 1.4779 | 0.0 |
238
+ | 0.8216 | 0.7936 | 18600 | 1.4465 | 0.0 |
239
+ | 0.7871 | 0.7978 | 18700 | 1.4819 | 0.0 |
240
+ | 0.7875 | 0.8021 | 18800 | 1.5598 | 0.0 |
241
+ | 0.8008 | 0.8064 | 18900 | 1.3580 | 0.0 |
242
+ | 0.7678 | 0.8106 | 19000 | 1.4929 | 0.0 |
243
+ | 0.7849 | 0.8149 | 19100 | 1.5162 | 0.0 |
244
+ | 0.7788 | 0.8192 | 19200 | 1.5648 | 0.0 |
245
+ | 0.7612 | 0.8234 | 19300 | 1.5605 | 0.0 |
246
+ | 0.7523 | 0.8277 | 19400 | 1.4789 | 0.0 |
247
+ | 0.7536 | 0.8320 | 19500 | 1.3515 | 0.0 |
248
+ | 0.7487 | 0.8362 | 19600 | 1.4554 | 0.0 |
249
+ | 0.7814 | 0.8405 | 19700 | 1.4210 | 0.0 |
250
+ | 0.8185 | 0.8448 | 19800 | 1.4865 | 0.0 |
251
+ | 0.7562 | 0.8490 | 19900 | 1.5305 | 0.0 |
252
+ | 0.7314 | 0.8533 | 20000 | 1.4015 | 0.0 |
253
+ | 0.8134 | 0.8576 | 20100 | 1.4826 | 0.0 |
254
+ | 0.7422 | 0.8618 | 20200 | 1.4742 | 0.0 |
255
+ | 0.7725 | 0.8661 | 20300 | 1.4381 | 0.0 |
256
+ | 0.7164 | 0.8704 | 20400 | 1.4728 | 0.0 |
257
+ | 0.7802 | 0.8746 | 20500 | 1.4851 | 0.0 |
258
+ | 0.7548 | 0.8789 | 20600 | 1.4551 | 0.0 |
259
+ | 0.7415 | 0.8832 | 20700 | 1.4340 | 0.0 |
260
+ | 0.7932 | 0.8874 | 20800 | 1.4658 | 0.0 |
261
+ | 0.7711 | 0.8917 | 20900 | 1.4571 | 0.0 |
262
+ | 0.7168 | 0.8960 | 21000 | 1.4991 | 0.0 |
263
+ | 0.7167 | 0.9002 | 21100 | 1.4291 | 0.0 |
264
+ | 0.7284 | 0.9045 | 21200 | 1.4307 | 0.0 |
265
+ | 0.7208 | 0.9088 | 21300 | 1.4494 | 0.0 |
266
+ | 0.7082 | 0.9130 | 21400 | 1.4404 | 0.0 |
267
+ | 0.7228 | 0.9173 | 21500 | 1.4215 | 0.0 |
268
+ | 0.679 | 0.9216 | 21600 | 1.4424 | 0.0 |
269
+ | 0.7194 | 0.9258 | 21700 | 1.4193 | 0.0 |
270
+ | 0.7363 | 0.9301 | 21800 | 1.4214 | 0.0 |
271
+ | 0.7382 | 0.9344 | 21900 | 1.4241 | 0.0 |
272
+ | 0.6975 | 0.9386 | 22000 | 1.4122 | 0.0 |
273
+ | 0.6855 | 0.9429 | 22100 | 1.4094 | 0.0 |
274
+ | 0.7273 | 0.9472 | 22200 | 1.4339 | 0.0 |
275
+ | 0.7336 | 0.9514 | 22300 | 1.4237 | 0.0 |
276
+ | 0.6451 | 0.9557 | 22400 | 1.4213 | 0.0 |
277
+ | 0.7041 | 0.9600 | 22500 | 1.4346 | 0.0 |
278
+ | 0.6902 | 0.9642 | 22600 | 1.4340 | 0.0 |
279
+ | 0.6788 | 0.9685 | 22700 | 1.4329 | 0.0 |
280
+ | 0.7087 | 0.9728 | 22800 | 1.4209 | 0.0 |
281
+ | 0.7652 | 0.9770 | 22900 | 1.4252 | 0.0 |
282
+ | 0.7478 | 0.9813 | 23000 | 1.4120 | 0.0 |
283
+ | 0.7473 | 0.9856 | 23100 | 1.4164 | 0.0 |
284
+ | 0.729 | 0.9898 | 23200 | 1.4210 | 0.0 |
285
+ | 0.6697 | 0.9941 | 23300 | 1.4209 | 0.0 |
286
+ | 0.703 | 0.9984 | 23400 | 1.4211 | 0.0 |
287
+
288
+
289
+ ### Framework versions
290
+
291
+ - Transformers 4.46.0
292
+ - Pytorch 2.5.1
293
+ - Datasets 3.1.0
294
+ - Tokenizers 0.20.1
config.json ADDED
@@ -0,0 +1,19 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "architectures": [
3
+ "NanoGPT"
4
+ ],
5
+ "bias": true,
6
+ "block_size": 256,
7
+ "dropout": 0.0,
8
+ "mlp_dim": 4,
9
+ "model_type": "nanogpt",
10
+ "n_embd": 384,
11
+ "n_head": 6,
12
+ "n_layer": 6,
13
+ "nonlinearity": "RELU",
14
+ "torch_dtype": "float32",
15
+ "transformers_version": "4.46.0",
16
+ "use_NoPE": true,
17
+ "use_layernorm": true,
18
+ "vocab_size": 106
19
+ }
generation_config.json ADDED
@@ -0,0 +1,4 @@
 
 
 
 
 
1
+ {
2
+ "_from_model_config": true,
3
+ "transformers_version": "4.46.0"
4
+ }
model.safetensors ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:6e614680650cd1ee825f74f3976c15e4c1bae85a1c0c054fed7d0fef43a83dc4
3
+ size 42923368
training_args.bin ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:c54c3050a738f82523684ff525e670a9a29bef8ce4c6314937c2e150b13ccdb0
3
+ size 5304