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augustocsc
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gpt2-10var

Text Generation
Transformers
PyTorch
gpt2
Generated from Trainer
text-generation-inference
Inference Endpoints
Model card Files Community
augustocsc commited on
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End of training

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  1. README.md +52 -127
  2. pytorch_model.bin +1 -1
README.md CHANGED
@@ -15,7 +15,7 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [gpt2](https://huggingface.co/gpt2) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.1086
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  ## Model description
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@@ -40,137 +40,62 @@ The following hyperparameters were used during training:
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  - seed: 42
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  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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  - lr_scheduler_type: linear
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- - num_epochs: 5
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss |
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  |:-------------:|:-----:|:-----:|:---------------:|
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- | No log | 0.04 | 200 | 0.2691 |
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- | No log | 0.08 | 400 | 1.5649 |
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- | 0.7894 | 0.12 | 600 | 0.4091 |
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- | 0.7894 | 0.16 | 800 | 0.4955 |
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- | 0.7504 | 0.2 | 1000 | 0.5257 |
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- | 0.7504 | 0.24 | 1200 | 0.6124 |
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- | 0.7504 | 0.28 | 1400 | 0.6224 |
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- | 0.7901 | 0.32 | 1600 | 0.5156 |
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- | 0.7901 | 0.36 | 1800 | 0.7702 |
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- | 0.7633 | 0.4 | 2000 | 0.8384 |
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- | 0.7633 | 0.44 | 2200 | 0.7715 |
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- | 0.7633 | 0.48 | 2400 | 0.8305 |
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- | 0.829 | 0.52 | 2600 | 0.8086 |
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- | 0.829 | 0.56 | 2800 | 0.9329 |
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- | 0.829 | 0.6 | 3000 | 0.8684 |
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- | 0.829 | 0.64 | 3200 | 0.9233 |
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- | 0.829 | 0.67 | 3400 | 0.8545 |
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- | 0.9221 | 0.71 | 3600 | 0.9147 |
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- | 0.9221 | 0.75 | 3800 | 0.8904 |
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- | 0.9301 | 0.79 | 4000 | 0.7672 |
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- | 0.9301 | 0.83 | 4200 | 0.9532 |
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- | 0.9301 | 0.87 | 4400 | 0.2594 |
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- | 1.5584 | 0.91 | 4600 | 0.1339 |
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- | 1.5584 | 0.95 | 4800 | 0.1273 |
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- | 0.135 | 0.99 | 5000 | 0.1184 |
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- | 0.135 | 1.03 | 5200 | 0.1163 |
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- | 0.135 | 1.07 | 5400 | 0.1157 |
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- | 0.1189 | 1.11 | 5600 | 0.1144 |
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- | 0.1189 | 1.15 | 5800 | 0.1136 |
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- | 0.1162 | 1.19 | 6000 | 0.1134 |
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- | 0.1162 | 1.23 | 6200 | 0.1130 |
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- | 0.1162 | 1.27 | 6400 | 0.1131 |
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- | 0.1165 | 1.31 | 6600 | 0.1123 |
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- | 0.1165 | 1.35 | 6800 | 0.1120 |
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- | 0.1136 | 1.39 | 7000 | 0.1116 |
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- | 0.1136 | 1.43 | 7200 | 0.1115 |
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- | 0.1136 | 1.47 | 7400 | 0.1111 |
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- | 0.1124 | 1.51 | 7600 | 0.1108 |
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- | 0.1124 | 1.55 | 7800 | 0.1110 |
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- | 0.1128 | 1.59 | 8000 | 0.1107 |
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- | 0.1128 | 1.63 | 8200 | 0.1104 |
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- | 0.1128 | 1.67 | 8400 | 0.1101 |
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- | 0.1114 | 1.71 | 8600 | 0.1103 |
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- | 0.1114 | 1.75 | 8800 | 0.1098 |
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- | 0.1094 | 1.79 | 9000 | 0.1101 |
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- | 0.1094 | 1.83 | 9200 | 0.1098 |
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- | 0.1094 | 1.87 | 9400 | 0.1098 |
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- | 0.111 | 1.91 | 9600 | 0.1106 |
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- | 0.111 | 1.94 | 9800 | 0.1100 |
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- | 0.1118 | 1.98 | 10000 | 0.1096 |
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- | 0.1118 | 2.02 | 10200 | 0.1096 |
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- | 0.1118 | 2.06 | 10400 | 0.1096 |
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- | 0.1102 | 2.1 | 10600 | 0.1094 |
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- | 0.1102 | 2.14 | 10800 | 0.1098 |
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- | 0.1083 | 2.18 | 11000 | 0.1093 |
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- | 0.1083 | 2.22 | 11200 | 0.1092 |
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- | 0.1083 | 2.26 | 11400 | 0.1093 |
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- | 0.1113 | 2.3 | 11600 | 0.1092 |
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- | 0.1113 | 2.34 | 11800 | 0.1092 |
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- | 0.1102 | 2.38 | 12000 | 0.1095 |
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- | 0.1102 | 2.42 | 12200 | 0.1091 |
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- | 0.1102 | 2.46 | 12400 | 0.1095 |
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- | 0.1093 | 2.5 | 12600 | 0.1091 |
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- | 0.1093 | 2.54 | 12800 | 0.1092 |
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- | 0.1105 | 2.58 | 13000 | 0.1091 |
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- | 0.1105 | 2.62 | 13200 | 0.1092 |
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- | 0.1105 | 2.66 | 13400 | 0.1091 |
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- | 0.1094 | 2.7 | 13600 | 0.1090 |
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- | 0.1094 | 2.74 | 13800 | 0.1089 |
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- | 0.1104 | 2.78 | 14000 | 0.1091 |
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- | 0.1104 | 2.82 | 14200 | 0.1090 |
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- | 0.1104 | 2.86 | 14400 | 0.1090 |
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- | 0.1117 | 2.9 | 14600 | 0.1090 |
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- | 0.1117 | 2.94 | 14800 | 0.1093 |
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- | 0.1093 | 2.98 | 15000 | 0.1090 |
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- | 0.1093 | 3.02 | 15200 | 0.1089 |
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- | 0.1093 | 3.06 | 15400 | 0.1088 |
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- | 0.1098 | 3.1 | 15600 | 0.1089 |
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- | 0.1098 | 3.14 | 15800 | 0.1089 |
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- | 0.1102 | 3.18 | 16000 | 0.1088 |
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- | 0.1102 | 3.21 | 16200 | 0.1088 |
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- | 0.1102 | 3.25 | 16400 | 0.1088 |
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- | 0.1087 | 3.29 | 16600 | 0.1088 |
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- | 0.1087 | 3.33 | 16800 | 0.1089 |
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- | 0.1082 | 3.37 | 17000 | 0.1089 |
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- | 0.1082 | 3.41 | 17200 | 0.1088 |
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- | 0.1082 | 3.45 | 17400 | 0.1088 |
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- | 0.1097 | 3.49 | 17600 | 0.1090 |
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- | 0.1097 | 3.53 | 17800 | 0.1088 |
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- | 0.1105 | 3.57 | 18000 | 0.1087 |
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- | 0.1105 | 3.61 | 18200 | 0.1088 |
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- | 0.1105 | 3.65 | 18400 | 0.1087 |
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- | 0.1089 | 3.69 | 18600 | 0.1087 |
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- | 0.1089 | 3.73 | 18800 | 0.1088 |
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- | 0.1101 | 3.77 | 19000 | 0.1087 |
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- | 0.1101 | 3.81 | 19200 | 0.1087 |
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- | 0.1101 | 3.85 | 19400 | 0.1087 |
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- | 0.1095 | 3.89 | 19600 | 0.1087 |
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- | 0.1095 | 3.93 | 19800 | 0.1087 |
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- | 0.1089 | 3.97 | 20000 | 0.1088 |
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- | 0.1089 | 4.01 | 20200 | 0.1087 |
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- | 0.1089 | 4.05 | 20400 | 0.1090 |
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- | 0.1093 | 4.09 | 20600 | 0.1087 |
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- | 0.1093 | 4.13 | 20800 | 0.1087 |
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- | 0.1091 | 4.17 | 21000 | 0.1087 |
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- | 0.1091 | 4.21 | 21200 | 0.1087 |
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- | 0.1091 | 4.25 | 21400 | 0.1087 |
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- | 0.11 | 4.29 | 21600 | 0.1086 |
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- | 0.11 | 4.33 | 21800 | 0.1087 |
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- | 0.11 | 4.37 | 22000 | 0.1088 |
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- | 0.11 | 4.41 | 22200 | 0.1087 |
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- | 0.11 | 4.45 | 22400 | 0.1086 |
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- | 0.1094 | 4.49 | 22600 | 0.1086 |
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- | 0.1094 | 4.52 | 22800 | 0.1086 |
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- | 0.1086 | 4.56 | 23000 | 0.1086 |
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- | 0.1086 | 4.6 | 23200 | 0.1086 |
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- | 0.1086 | 4.64 | 23400 | 0.1086 |
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- | 0.1087 | 4.68 | 23600 | 0.1086 |
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- | 0.1087 | 4.72 | 23800 | 0.1086 |
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- | 0.1105 | 4.76 | 24000 | 0.1086 |
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- | 0.1105 | 4.8 | 24200 | 0.1086 |
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- | 0.1105 | 4.84 | 24400 | 0.1086 |
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- | 0.1092 | 4.88 | 24600 | 0.1086 |
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- | 0.1092 | 4.92 | 24800 | 0.1086 |
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- | 0.108 | 4.96 | 25000 | 0.1086 |
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  ### Framework versions
 
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  This model is a fine-tuned version of [gpt2](https://huggingface.co/gpt2) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.1102
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  ## Model description
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  - seed: 42
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  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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  - lr_scheduler_type: linear
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+ - num_epochs: 2
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss |
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  |:-------------:|:-----:|:-----:|:---------------:|
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+ | No log | 0.04 | 200 | 0.2493 |
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+ | No log | 0.08 | 400 | 0.3971 |
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+ | 0.4919 | 0.12 | 600 | 0.6197 |
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+ | 0.4919 | 0.16 | 800 | 0.5482 |
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+ | 0.9307 | 0.2 | 1000 | 0.8619 |
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+ | 0.9307 | 0.24 | 1200 | 0.5619 |
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+ | 0.9307 | 0.28 | 1400 | 0.7757 |
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+ | 1.6552 | 0.32 | 1600 | 0.5050 |
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+ | 1.6552 | 0.36 | 1800 | 1.1518 |
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+ | 1.1387 | 0.4 | 2000 | 1.0939 |
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+ | 1.1387 | 0.44 | 2200 | 9.2829 |
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+ | 1.1387 | 0.48 | 2400 | 0.2714 |
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+ | 8.5966 | 0.52 | 2600 | 0.1263 |
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+ | 8.5966 | 0.56 | 2800 | 0.1191 |
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+ | 0.1233 | 0.6 | 3000 | 0.1161 |
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+ | 0.1233 | 0.64 | 3200 | 0.1150 |
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+ | 0.1233 | 0.67 | 3400 | 0.1145 |
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+ | 0.1166 | 0.71 | 3600 | 0.1138 |
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+ | 0.1166 | 0.75 | 3800 | 0.1135 |
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+ | 0.1151 | 0.79 | 4000 | 0.1132 |
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+ | 0.1151 | 0.83 | 4200 | 0.1130 |
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+ | 0.1151 | 0.87 | 4400 | 0.1125 |
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+ | 0.1131 | 0.91 | 4600 | 0.1122 |
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+ | 0.1131 | 0.95 | 4800 | 0.1119 |
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+ | 0.1132 | 0.99 | 5000 | 0.1116 |
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+ | 0.1132 | 1.03 | 5200 | 0.1115 |
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+ | 0.1132 | 1.07 | 5400 | 0.1115 |
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+ | 0.1123 | 1.11 | 5600 | 0.1112 |
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+ | 0.1123 | 1.15 | 5800 | 0.1111 |
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+ | 0.1116 | 1.19 | 6000 | 0.1110 |
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+ | 0.1116 | 1.23 | 6200 | 0.1110 |
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+ | 0.1116 | 1.27 | 6400 | 0.1108 |
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+ | 0.1132 | 1.31 | 6600 | 0.1107 |
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+ | 0.1132 | 1.35 | 6800 | 0.1122 |
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+ | 0.2039 | 1.39 | 7000 | 0.1110 |
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+ | 0.2039 | 1.43 | 7200 | 0.1108 |
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+ | 0.2039 | 1.47 | 7400 | 0.1106 |
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+ | 0.1107 | 1.51 | 7600 | 0.1106 |
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+ | 0.1107 | 1.55 | 7800 | 0.1105 |
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+ | 0.1115 | 1.59 | 8000 | 0.1104 |
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+ | 0.1115 | 1.63 | 8200 | 0.1104 |
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+ | 0.1115 | 1.67 | 8400 | 0.1104 |
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+ | 0.1106 | 1.71 | 8600 | 0.1104 |
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+ | 0.1106 | 1.75 | 8800 | 0.1103 |
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+ | 0.1092 | 1.79 | 9000 | 0.1103 |
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+ | 0.1092 | 1.83 | 9200 | 0.1103 |
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+ | 0.1092 | 1.87 | 9400 | 0.1102 |
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+ | 0.111 | 1.91 | 9600 | 0.1102 |
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+ | 0.111 | 1.94 | 9800 | 0.1102 |
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+ | 0.1109 | 1.98 | 10000 | 0.1102 |
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ### Framework versions
pytorch_model.bin CHANGED
@@ -1,3 +1,3 @@
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