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End of training

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  1. README.md +166 -15
  2. tokenizer.json +1 -6
README.md CHANGED
@@ -3,6 +3,8 @@ license: apache-2.0
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  base_model: google/flan-t5-base
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  tags:
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  - generated_from_trainer
 
 
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  model-index:
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  - name: flan-t5-base-spelling
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  results: []
@@ -15,17 +17,12 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [google/flan-t5-base](https://huggingface.co/google/flan-t5-base) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - eval_loss: 0.3170
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- - eval_rouge1: 74.8776
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- - eval_rouge2: 70.3187
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- - eval_rougeL: 74.6212
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- - eval_rougeLsum: 74.6923
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- - eval_gen_len: 18.72
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- - eval_runtime: 4.3823
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- - eval_samples_per_second: 22.819
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- - eval_steps_per_second: 2.282
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- - epoch: 0.03
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- - step: 500
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  ## Model description
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@@ -45,15 +42,169 @@ More information needed
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  The following hyperparameters were used during training:
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  - learning_rate: 0.0001
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- - train_batch_size: 10
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- - eval_batch_size: 10
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  - seed: 42
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- - gradient_accumulation_steps: 4
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- - total_train_batch_size: 40
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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: 1
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57
  ### Framework versions
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  - Transformers 4.35.2
 
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  base_model: google/flan-t5-base
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  tags:
5
  - generated_from_trainer
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+ metrics:
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+ - rouge
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  model-index:
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  - name: flan-t5-base-spelling
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  results: []
 
17
 
18
  This model is a fine-tuned version of [google/flan-t5-base](https://huggingface.co/google/flan-t5-base) on an unknown dataset.
19
  It achieves the following results on the evaluation set:
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+ - Loss: 0.3014
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+ - Rouge1: 95.6848
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+ - Rouge2: 91.5839
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+ - Rougel: 95.679
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+ - Rougelsum: 95.6777
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+ - Gen Len: 33.54
 
 
 
 
 
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  ## Model description
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42
 
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  The following hyperparameters were used during training:
44
  - learning_rate: 0.0001
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+ - train_batch_size: 4
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+ - eval_batch_size: 4
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  - seed: 42
 
 
48
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
49
  - lr_scheduler_type: linear
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  - num_epochs: 1
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52
+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
55
+ |:-------------:|:-----:|:------:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
56
+ | 0.412 | 0.01 | 1000 | 0.3298 | 95.7852 | 91.7559 | 95.7602 | 95.7515 | 33.6 |
57
+ | 0.3593 | 0.01 | 2000 | 0.3301 | 95.8348 | 91.8272 | 95.8136 | 95.8144 | 33.55 |
58
+ | 0.3558 | 0.02 | 3000 | 0.3235 | 95.7455 | 91.6348 | 95.7048 | 95.7262 | 33.51 |
59
+ | 0.3242 | 0.03 | 4000 | 0.3359 | 95.863 | 91.8177 | 95.8296 | 95.8436 | 33.49 |
60
+ | 0.313 | 0.03 | 5000 | 0.3359 | 95.6728 | 91.4223 | 95.6613 | 95.6584 | 33.54 |
61
+ | 0.3123 | 0.04 | 6000 | 0.3441 | 95.8138 | 91.8344 | 95.7997 | 95.8025 | 33.6 |
62
+ | 0.3099 | 0.05 | 7000 | 0.3321 | 95.8138 | 91.8344 | 95.7997 | 95.8025 | 33.62 |
63
+ | 0.2958 | 0.05 | 8000 | 0.3269 | 95.8108 | 91.664 | 95.7949 | 95.7904 | 33.54 |
64
+ | 0.2749 | 0.06 | 9000 | 0.3237 | 95.758 | 91.7913 | 95.7622 | 95.7659 | 33.59 |
65
+ | 0.2841 | 0.07 | 10000 | 0.3114 | 95.8508 | 91.8853 | 95.8329 | 95.832 | 33.51 |
66
+ | 0.2772 | 0.07 | 11000 | 0.3206 | 95.8584 | 91.9881 | 95.853 | 95.864 | 33.54 |
67
+ | 0.2875 | 0.08 | 12000 | 0.3164 | 95.824 | 91.8821 | 95.8201 | 95.8307 | 33.56 |
68
+ | 0.3008 | 0.09 | 13000 | 0.3202 | 95.9349 | 92.075 | 95.9245 | 95.9207 | 33.55 |
69
+ | 0.288 | 0.09 | 14000 | 0.3140 | 95.7841 | 91.7283 | 95.7548 | 95.7585 | 33.42 |
70
+ | 0.2866 | 0.1 | 15000 | 0.3207 | 95.8259 | 91.8816 | 95.8057 | 95.8181 | 33.57 |
71
+ | 0.284 | 0.11 | 16000 | 0.3177 | 95.8209 | 91.8465 | 95.7971 | 95.7896 | 33.59 |
72
+ | 0.2574 | 0.11 | 17000 | 0.3146 | 95.8119 | 91.8995 | 95.7928 | 95.794 | 33.55 |
73
+ | 0.2807 | 0.12 | 18000 | 0.3214 | 95.7925 | 91.8605 | 95.769 | 95.7734 | 33.55 |
74
+ | 0.2742 | 0.13 | 19000 | 0.3185 | 95.8752 | 91.9684 | 95.8473 | 95.8513 | 33.49 |
75
+ | 0.2784 | 0.13 | 20000 | 0.3237 | 95.8729 | 92.0086 | 95.8636 | 95.8659 | 33.53 |
76
+ | 0.2768 | 0.14 | 21000 | 0.3187 | 95.6921 | 91.5779 | 95.6763 | 95.6681 | 33.44 |
77
+ | 0.2789 | 0.15 | 22000 | 0.3245 | 95.786 | 91.8861 | 95.7659 | 95.7607 | 33.5 |
78
+ | 0.2422 | 0.15 | 23000 | 0.3285 | 95.8421 | 91.9532 | 95.8388 | 95.8337 | 33.59 |
79
+ | 0.2838 | 0.16 | 24000 | 0.3186 | 95.5789 | 91.3976 | 95.5557 | 95.5694 | 33.56 |
80
+ | 0.2603 | 0.17 | 25000 | 0.3268 | 95.7276 | 91.6634 | 95.7156 | 95.7154 | 33.55 |
81
+ | 0.2622 | 0.17 | 26000 | 0.3230 | 95.808 | 91.9242 | 95.8018 | 95.7992 | 33.58 |
82
+ | 0.264 | 0.18 | 27000 | 0.3143 | 95.7982 | 91.8439 | 95.803 | 95.7941 | 33.6 |
83
+ | 0.26 | 0.19 | 28000 | 0.3245 | 95.7435 | 91.7233 | 95.7274 | 95.7203 | 33.6 |
84
+ | 0.2644 | 0.19 | 29000 | 0.3173 | 95.7982 | 91.8439 | 95.803 | 95.7941 | 33.56 |
85
+ | 0.2619 | 0.2 | 30000 | 0.3234 | 95.6744 | 91.5742 | 95.669 | 95.6593 | 33.57 |
86
+ | 0.2621 | 0.21 | 31000 | 0.3211 | 95.8658 | 91.9664 | 95.8593 | 95.8504 | 33.56 |
87
+ | 0.247 | 0.21 | 32000 | 0.3232 | 95.7248 | 91.4886 | 95.7127 | 95.7006 | 33.57 |
88
+ | 0.2428 | 0.22 | 33000 | 0.3206 | 95.8412 | 91.9314 | 95.8346 | 95.826 | 33.56 |
89
+ | 0.2389 | 0.23 | 34000 | 0.3125 | 95.7443 | 91.724 | 95.7435 | 95.7439 | 33.57 |
90
+ | 0.2634 | 0.23 | 35000 | 0.3205 | 95.8085 | 91.863 | 95.8091 | 95.805 | 33.56 |
91
+ | 0.2552 | 0.24 | 36000 | 0.3112 | 95.7519 | 91.7062 | 95.7286 | 95.744 | 33.54 |
92
+ | 0.2554 | 0.25 | 37000 | 0.3141 | 95.736 | 91.7453 | 95.7348 | 95.7258 | 33.56 |
93
+ | 0.2587 | 0.25 | 38000 | 0.3140 | 95.7572 | 91.6578 | 95.7428 | 95.7436 | 33.48 |
94
+ | 0.2521 | 0.26 | 39000 | 0.3146 | 95.7416 | 91.4858 | 95.7294 | 95.7293 | 33.47 |
95
+ | 0.2625 | 0.27 | 40000 | 0.3175 | 95.69 | 91.5155 | 95.6853 | 95.6856 | 33.53 |
96
+ | 0.2459 | 0.27 | 41000 | 0.3094 | 95.7464 | 91.7371 | 95.7353 | 95.7386 | 33.57 |
97
+ | 0.245 | 0.28 | 42000 | 0.3132 | 95.7602 | 91.7861 | 95.7498 | 95.7554 | 33.61 |
98
+ | 0.2403 | 0.29 | 43000 | 0.3169 | 95.6634 | 91.593 | 95.6744 | 95.6835 | 33.57 |
99
+ | 0.2516 | 0.29 | 44000 | 0.3146 | 95.6702 | 91.4878 | 95.6453 | 95.6495 | 33.53 |
100
+ | 0.2463 | 0.3 | 45000 | 0.3082 | 95.6617 | 91.5631 | 95.6687 | 95.6628 | 33.61 |
101
+ | 0.23 | 0.31 | 46000 | 0.3109 | 95.7859 | 91.8242 | 95.7675 | 95.7743 | 33.55 |
102
+ | 0.2486 | 0.31 | 47000 | 0.3116 | 95.8384 | 91.8854 | 95.8349 | 95.8324 | 33.5 |
103
+ | 0.249 | 0.32 | 48000 | 0.3129 | 95.7614 | 91.7998 | 95.7548 | 95.7663 | 33.53 |
104
+ | 0.2285 | 0.33 | 49000 | 0.3149 | 95.7684 | 91.7453 | 95.7513 | 95.761 | 33.56 |
105
+ | 0.2447 | 0.33 | 50000 | 0.3133 | 95.7226 | 91.7332 | 95.7089 | 95.7118 | 33.55 |
106
+ | 0.2374 | 0.34 | 51000 | 0.3096 | 95.7373 | 91.772 | 95.7205 | 95.7261 | 33.57 |
107
+ | 0.2361 | 0.35 | 52000 | 0.3156 | 95.8283 | 92.0269 | 95.8162 | 95.8259 | 33.6 |
108
+ | 0.2408 | 0.35 | 53000 | 0.3098 | 95.6854 | 91.7511 | 95.6702 | 95.6927 | 33.63 |
109
+ | 0.2419 | 0.36 | 54000 | 0.3140 | 95.5872 | 91.3338 | 95.5907 | 95.6066 | 33.54 |
110
+ | 0.2436 | 0.37 | 55000 | 0.3134 | 95.7498 | 91.8573 | 95.7465 | 95.7411 | 33.54 |
111
+ | 0.2396 | 0.37 | 56000 | 0.3138 | 95.7169 | 91.7169 | 95.698 | 95.7106 | 33.51 |
112
+ | 0.2315 | 0.38 | 57000 | 0.3122 | 95.809 | 91.9188 | 95.8006 | 95.7915 | 33.49 |
113
+ | 0.2298 | 0.39 | 58000 | 0.3181 | 95.6967 | 91.6519 | 95.6813 | 95.6906 | 33.49 |
114
+ | 0.2345 | 0.39 | 59000 | 0.3173 | 95.7213 | 91.6964 | 95.7225 | 95.7077 | 33.5 |
115
+ | 0.2323 | 0.4 | 60000 | 0.3169 | 95.6666 | 91.543 | 95.6482 | 95.6599 | 33.58 |
116
+ | 0.236 | 0.41 | 61000 | 0.3164 | 95.7845 | 91.8149 | 95.7699 | 95.7677 | 33.56 |
117
+ | 0.2246 | 0.41 | 62000 | 0.3110 | 95.6412 | 91.4598 | 95.6383 | 95.6356 | 33.5 |
118
+ | 0.2267 | 0.42 | 63000 | 0.3088 | 95.7137 | 91.6683 | 95.706 | 95.7034 | 33.53 |
119
+ | 0.232 | 0.43 | 64000 | 0.3105 | 95.7599 | 91.7777 | 95.7602 | 95.7566 | 33.56 |
120
+ | 0.2123 | 0.43 | 65000 | 0.3082 | 95.6892 | 91.6144 | 95.6855 | 95.6935 | 33.57 |
121
+ | 0.2195 | 0.44 | 66000 | 0.3053 | 95.7095 | 91.7089 | 95.7063 | 95.7029 | 33.54 |
122
+ | 0.2434 | 0.45 | 67000 | 0.3093 | 95.8082 | 91.8858 | 95.7912 | 95.7946 | 33.52 |
123
+ | 0.2336 | 0.45 | 68000 | 0.3050 | 95.814 | 91.8745 | 95.8045 | 95.7973 | 33.55 |
124
+ | 0.2326 | 0.46 | 69000 | 0.3029 | 95.7247 | 91.7338 | 95.7163 | 95.7136 | 33.51 |
125
+ | 0.2454 | 0.47 | 70000 | 0.3123 | 95.7778 | 91.7202 | 95.7531 | 95.7492 | 33.48 |
126
+ | 0.2402 | 0.47 | 71000 | 0.3090 | 95.7694 | 91.6795 | 95.766 | 95.7524 | 33.47 |
127
+ | 0.2233 | 0.48 | 72000 | 0.3100 | 95.7594 | 91.7237 | 95.7389 | 95.7391 | 33.53 |
128
+ | 0.2199 | 0.49 | 73000 | 0.3135 | 95.7177 | 91.6686 | 95.7014 | 95.7123 | 33.47 |
129
+ | 0.2205 | 0.49 | 74000 | 0.3116 | 95.714 | 91.5665 | 95.7022 | 95.7061 | 33.51 |
130
+ | 0.2178 | 0.5 | 75000 | 0.3120 | 95.7485 | 91.6867 | 95.7277 | 95.7411 | 33.54 |
131
+ | 0.2226 | 0.51 | 76000 | 0.3130 | 95.7285 | 91.6919 | 95.7199 | 95.7192 | 33.5 |
132
+ | 0.2199 | 0.51 | 77000 | 0.3123 | 95.7969 | 91.8832 | 95.7934 | 95.7782 | 33.48 |
133
+ | 0.2177 | 0.52 | 78000 | 0.3090 | 95.7166 | 91.7218 | 95.7148 | 95.7098 | 33.55 |
134
+ | 0.216 | 0.53 | 79000 | 0.3024 | 95.6977 | 91.689 | 95.7016 | 95.6875 | 33.53 |
135
+ | 0.2252 | 0.53 | 80000 | 0.3057 | 95.6664 | 91.6233 | 95.6616 | 95.6674 | 33.54 |
136
+ | 0.2209 | 0.54 | 81000 | 0.3057 | 95.4622 | 91.2615 | 95.4438 | 95.4563 | 33.54 |
137
+ | 0.2134 | 0.55 | 82000 | 0.3107 | 95.6903 | 91.6428 | 95.686 | 95.6862 | 33.53 |
138
+ | 0.2174 | 0.55 | 83000 | 0.3078 | 95.7232 | 91.6865 | 95.7109 | 95.7141 | 33.58 |
139
+ | 0.2217 | 0.56 | 84000 | 0.3062 | 95.6664 | 91.6233 | 95.6616 | 95.6674 | 33.55 |
140
+ | 0.2186 | 0.57 | 85000 | 0.3096 | 95.5492 | 91.3676 | 95.5382 | 95.5372 | 33.54 |
141
+ | 0.2192 | 0.57 | 86000 | 0.3070 | 95.6729 | 91.4616 | 95.6675 | 95.6665 | 33.52 |
142
+ | 0.2315 | 0.58 | 87000 | 0.3034 | 95.5492 | 91.3676 | 95.5382 | 95.5372 | 33.54 |
143
+ | 0.2248 | 0.59 | 88000 | 0.3023 | 95.7411 | 91.6705 | 95.7342 | 95.7318 | 33.55 |
144
+ | 0.2193 | 0.59 | 89000 | 0.3061 | 95.7364 | 91.709 | 95.7285 | 95.7354 | 33.57 |
145
+ | 0.2212 | 0.6 | 90000 | 0.3061 | 95.6604 | 91.5168 | 95.6399 | 95.6356 | 33.57 |
146
+ | 0.2287 | 0.61 | 91000 | 0.3073 | 95.7703 | 91.7829 | 95.7669 | 95.7617 | 33.57 |
147
+ | 0.239 | 0.61 | 92000 | 0.3063 | 95.7232 | 91.6865 | 95.7109 | 95.7141 | 33.59 |
148
+ | 0.2113 | 0.62 | 93000 | 0.3123 | 95.6757 | 91.4957 | 95.6738 | 95.6683 | 33.56 |
149
+ | 0.2259 | 0.63 | 94000 | 0.3110 | 95.6757 | 91.4957 | 95.6738 | 95.6683 | 33.56 |
150
+ | 0.2178 | 0.63 | 95000 | 0.3142 | 95.6548 | 91.4577 | 95.6529 | 95.6478 | 33.57 |
151
+ | 0.2288 | 0.64 | 96000 | 0.3051 | 95.7232 | 91.6865 | 95.7109 | 95.7141 | 33.59 |
152
+ | 0.2051 | 0.65 | 97000 | 0.3073 | 95.761 | 91.7916 | 95.7624 | 95.7573 | 33.59 |
153
+ | 0.2227 | 0.65 | 98000 | 0.3091 | 95.6803 | 91.526 | 95.6722 | 95.6768 | 33.56 |
154
+ | 0.2353 | 0.66 | 99000 | 0.3087 | 95.662 | 91.4535 | 95.6541 | 95.6524 | 33.55 |
155
+ | 0.217 | 0.67 | 100000 | 0.3046 | 95.6757 | 91.4957 | 95.6738 | 95.6683 | 33.56 |
156
+ | 0.1989 | 0.67 | 101000 | 0.3062 | 95.6757 | 91.4957 | 95.6738 | 95.6683 | 33.56 |
157
+ | 0.217 | 0.68 | 102000 | 0.3071 | 95.6757 | 91.4957 | 95.6738 | 95.6683 | 33.56 |
158
+ | 0.22 | 0.69 | 103000 | 0.3048 | 95.6757 | 91.4957 | 95.6738 | 95.6683 | 33.56 |
159
+ | 0.2202 | 0.69 | 104000 | 0.3081 | 95.6757 | 91.4957 | 95.6738 | 95.6683 | 33.56 |
160
+ | 0.2121 | 0.7 | 105000 | 0.3088 | 95.6265 | 91.4405 | 95.6194 | 95.6178 | 33.54 |
161
+ | 0.2137 | 0.71 | 106000 | 0.3096 | 95.7694 | 91.6795 | 95.766 | 95.7524 | 33.49 |
162
+ | 0.2261 | 0.71 | 107000 | 0.3041 | 95.7209 | 91.6199 | 95.7148 | 95.7064 | 33.47 |
163
+ | 0.2105 | 0.72 | 108000 | 0.3042 | 95.7209 | 91.6199 | 95.7148 | 95.7064 | 33.47 |
164
+ | 0.1974 | 0.73 | 109000 | 0.3045 | 95.6593 | 91.5597 | 95.656 | 95.6542 | 33.53 |
165
+ | 0.198 | 0.73 | 110000 | 0.3054 | 95.7694 | 91.6795 | 95.766 | 95.7524 | 33.49 |
166
+ | 0.2217 | 0.74 | 111000 | 0.3049 | 95.7102 | 91.6135 | 95.7119 | 95.7038 | 33.55 |
167
+ | 0.225 | 0.75 | 112000 | 0.3021 | 95.7102 | 91.6135 | 95.7119 | 95.7038 | 33.55 |
168
+ | 0.2222 | 0.75 | 113000 | 0.3045 | 95.7102 | 91.6135 | 95.7119 | 95.7038 | 33.55 |
169
+ | 0.2078 | 0.76 | 114000 | 0.3041 | 95.7102 | 91.6135 | 95.7119 | 95.7038 | 33.55 |
170
+ | 0.2194 | 0.77 | 115000 | 0.3027 | 95.7102 | 91.6135 | 95.7119 | 95.7038 | 33.55 |
171
+ | 0.2155 | 0.77 | 116000 | 0.3037 | 95.6593 | 91.5597 | 95.656 | 95.6542 | 33.53 |
172
+ | 0.2201 | 0.78 | 117000 | 0.3007 | 95.7102 | 91.6135 | 95.7119 | 95.7038 | 33.55 |
173
+ | 0.2061 | 0.79 | 118000 | 0.3017 | 95.7102 | 91.6135 | 95.7119 | 95.7038 | 33.55 |
174
+ | 0.2091 | 0.79 | 119000 | 0.3021 | 95.7102 | 91.6135 | 95.7119 | 95.7038 | 33.55 |
175
+ | 0.1921 | 0.8 | 120000 | 0.3036 | 95.7102 | 91.6135 | 95.7119 | 95.7038 | 33.55 |
176
+ | 0.2013 | 0.81 | 121000 | 0.3033 | 95.7102 | 91.6135 | 95.7119 | 95.7038 | 33.55 |
177
+ | 0.2105 | 0.81 | 122000 | 0.3003 | 95.6511 | 91.473 | 95.6445 | 95.6453 | 33.54 |
178
+ | 0.2044 | 0.82 | 123000 | 0.2997 | 95.6511 | 91.473 | 95.6445 | 95.6453 | 33.55 |
179
+ | 0.2128 | 0.83 | 124000 | 0.2997 | 95.6511 | 91.473 | 95.6445 | 95.6453 | 33.55 |
180
+ | 0.2113 | 0.83 | 125000 | 0.3016 | 95.6317 | 91.4265 | 95.6215 | 95.6277 | 33.55 |
181
+ | 0.2078 | 0.84 | 126000 | 0.3003 | 95.6317 | 91.4265 | 95.6215 | 95.6277 | 33.55 |
182
+ | 0.2117 | 0.85 | 127000 | 0.3016 | 95.6511 | 91.473 | 95.6445 | 95.6453 | 33.55 |
183
+ | 0.2112 | 0.85 | 128000 | 0.3012 | 95.5576 | 91.1912 | 95.5377 | 95.5468 | 33.52 |
184
+ | 0.2035 | 0.86 | 129000 | 0.3018 | 95.6286 | 91.3629 | 95.608 | 95.6137 | 33.49 |
185
+ | 0.2228 | 0.87 | 130000 | 0.2999 | 95.6511 | 91.473 | 95.6445 | 95.6453 | 33.55 |
186
+ | 0.2079 | 0.87 | 131000 | 0.2999 | 95.6511 | 91.473 | 95.6445 | 95.6453 | 33.55 |
187
+ | 0.2145 | 0.88 | 132000 | 0.3004 | 95.6409 | 91.4248 | 95.6233 | 95.6332 | 33.53 |
188
+ | 0.1987 | 0.89 | 133000 | 0.3028 | 95.6409 | 91.4248 | 95.6233 | 95.6332 | 33.53 |
189
+ | 0.2045 | 0.89 | 134000 | 0.3043 | 95.6848 | 91.5839 | 95.679 | 95.6777 | 33.54 |
190
+ | 0.1922 | 0.9 | 135000 | 0.3014 | 95.6313 | 91.4632 | 95.6214 | 95.6226 | 33.52 |
191
+ | 0.1956 | 0.91 | 136000 | 0.3003 | 95.6313 | 91.4632 | 95.6214 | 95.6226 | 33.52 |
192
+ | 0.2132 | 0.91 | 137000 | 0.3001 | 95.6848 | 91.5839 | 95.679 | 95.6777 | 33.54 |
193
+ | 0.1989 | 0.92 | 138000 | 0.2998 | 95.6409 | 91.4248 | 95.6233 | 95.6332 | 33.53 |
194
+ | 0.2179 | 0.93 | 139000 | 0.2997 | 95.6409 | 91.4248 | 95.6233 | 95.6332 | 33.53 |
195
+ | 0.1921 | 0.93 | 140000 | 0.2994 | 95.6848 | 91.5839 | 95.679 | 95.6777 | 33.54 |
196
+ | 0.2031 | 0.94 | 141000 | 0.3003 | 95.6848 | 91.5839 | 95.679 | 95.6777 | 33.54 |
197
+ | 0.1961 | 0.95 | 142000 | 0.3021 | 95.6848 | 91.5839 | 95.679 | 95.6777 | 33.54 |
198
+ | 0.2166 | 0.95 | 143000 | 0.3023 | 95.6848 | 91.5839 | 95.679 | 95.6777 | 33.54 |
199
+ | 0.2105 | 0.96 | 144000 | 0.3021 | 95.6848 | 91.5839 | 95.679 | 95.6777 | 33.54 |
200
+ | 0.2244 | 0.97 | 145000 | 0.3019 | 95.6848 | 91.5839 | 95.679 | 95.6777 | 33.54 |
201
+ | 0.1998 | 0.97 | 146000 | 0.3017 | 95.6848 | 91.5839 | 95.679 | 95.6777 | 33.54 |
202
+ | 0.2001 | 0.98 | 147000 | 0.3016 | 95.6848 | 91.5839 | 95.679 | 95.6777 | 33.54 |
203
+ | 0.2152 | 0.99 | 148000 | 0.3015 | 95.6848 | 91.5839 | 95.679 | 95.6777 | 33.54 |
204
+ | 0.1987 | 0.99 | 149000 | 0.3014 | 95.6848 | 91.5839 | 95.679 | 95.6777 | 33.54 |
205
+ | 0.2068 | 1.0 | 150000 | 0.3014 | 95.6848 | 91.5839 | 95.679 | 95.6777 | 33.54 |
206
+
207
+
208
  ### Framework versions
209
 
210
  - Transformers 4.35.2
tokenizer.json CHANGED
@@ -1,11 +1,6 @@
1
  {
2
  "version": "1.0",
3
- "truncation": {
4
- "direction": "Right",
5
- "max_length": 512,
6
- "strategy": "LongestFirst",
7
- "stride": 0
8
- },
9
  "padding": null,
10
  "added_tokens": [
11
  {
 
1
  {
2
  "version": "1.0",
3
+ "truncation": null,
 
 
 
 
 
4
  "padding": null,
5
  "added_tokens": [
6
  {