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@@ -2,8 +2,6 @@
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  license: apache-2.0
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  base_model: facebook/wav2vec2-large-xlsr-53
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  tags:
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- - automatic-speech-recognition
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- - DewiBrynJones/banc-trawsgrifiadau-bangor-clean-with-ccv
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  - generated_from_trainer
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  metrics:
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  - wer
@@ -17,10 +15,10 @@ should probably proofread and complete it, then remove this comment. -->
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18
  # wav2vec2-xlsr-53-ft-btb-ccv-cy
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20
- This model is a fine-tuned version of [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on the DEWIBRYNJONES/BANC-TRAWSGRIFIADAU-BANGOR-CLEAN-WITH-CCV - DEFAULT dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.4908
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- - Wer: 0.3964
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25
  ## Model description
26
 
@@ -46,113 +44,163 @@ The following hyperparameters were used during training:
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  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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  - lr_scheduler_type: linear
48
  - lr_scheduler_warmup_steps: 500
49
- - training_steps: 20000
50
  - mixed_precision_training: Native AMP
51
 
52
  ### Training results
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54
  | Training Loss | Epoch | Step | Validation Loss | Wer |
55
  |:-------------:|:------:|:-----:|:---------------:|:------:|
56
- | No log | 0.0079 | 200 | 3.1856 | 1.0 |
57
- | No log | 0.0157 | 400 | 2.6492 | 1.0 |
58
- | 4.6997 | 0.0236 | 600 | 1.3869 | 0.8722 |
59
- | 4.6997 | 0.0314 | 800 | 1.2302 | 0.8308 |
60
- | 1.0569 | 0.0393 | 1000 | 1.1380 | 0.7958 |
61
- | 1.0569 | 0.0472 | 1200 | 1.0668 | 0.7698 |
62
- | 1.0569 | 0.0550 | 1400 | 1.0208 | 0.7310 |
63
- | 0.8131 | 0.0629 | 1600 | 0.9702 | 0.7151 |
64
- | 0.8131 | 0.0707 | 1800 | 0.9408 | 0.6882 |
65
- | 0.7194 | 0.0786 | 2000 | 0.9250 | 0.6804 |
66
- | 0.7194 | 0.0864 | 2200 | 0.9052 | 0.6726 |
67
- | 0.7194 | 0.0943 | 2400 | 0.8986 | 0.6573 |
68
- | 0.6688 | 0.1022 | 2600 | 0.8815 | 0.6473 |
69
- | 0.6688 | 0.1100 | 2800 | 0.8588 | 0.6445 |
70
- | 0.645 | 0.1179 | 3000 | 0.8758 | 0.6487 |
71
- | 0.645 | 0.1257 | 3200 | 0.8725 | 0.6691 |
72
- | 0.645 | 0.1336 | 3400 | 0.8296 | 0.6298 |
73
- | 0.6077 | 0.1415 | 3600 | 0.8356 | 0.6552 |
74
- | 0.6077 | 0.1493 | 3800 | 0.8263 | 0.6229 |
75
- | 0.5983 | 0.1572 | 4000 | 0.8711 | 0.6885 |
76
- | 0.5983 | 0.1650 | 4200 | 0.7837 | 0.5918 |
77
- | 0.5983 | 0.1729 | 4400 | 0.8097 | 0.6598 |
78
- | 0.5788 | 0.1808 | 4600 | 0.7777 | 0.5869 |
79
- | 0.5788 | 0.1886 | 4800 | 0.7913 | 0.5896 |
80
- | 0.5501 | 0.1965 | 5000 | 0.7924 | 0.5900 |
81
- | 0.5501 | 0.2043 | 5200 | 0.7603 | 0.5737 |
82
- | 0.5501 | 0.2122 | 5400 | 0.7750 | 0.5932 |
83
- | 0.5694 | 0.2200 | 5600 | 0.7517 | 0.5711 |
84
- | 0.5694 | 0.2279 | 5800 | 0.7651 | 0.5698 |
85
- | 0.5424 | 0.2358 | 6000 | 0.7548 | 0.5820 |
86
- | 0.5424 | 0.2436 | 6200 | 0.7305 | 0.5681 |
87
- | 0.5424 | 0.2515 | 6400 | 0.7314 | 0.5589 |
88
- | 0.521 | 0.2593 | 6600 | 0.7228 | 0.5654 |
89
- | 0.521 | 0.2672 | 6800 | 0.7350 | 0.5633 |
90
- | 0.5119 | 0.2751 | 7000 | 0.7079 | 0.5347 |
91
- | 0.5119 | 0.2829 | 7200 | 0.7105 | 0.5601 |
92
- | 0.5119 | 0.2908 | 7400 | 0.6876 | 0.5378 |
93
- | 0.5007 | 0.2986 | 7600 | 0.6835 | 0.5303 |
94
- | 0.5007 | 0.3065 | 7800 | 0.7132 | 0.5351 |
95
- | 0.4934 | 0.3144 | 8000 | 0.6972 | 0.5242 |
96
- | 0.4934 | 0.3222 | 8200 | 0.6800 | 0.5227 |
97
- | 0.4934 | 0.3301 | 8400 | 0.6916 | 0.5365 |
98
- | 0.4762 | 0.3379 | 8600 | 0.6802 | 0.5255 |
99
- | 0.4762 | 0.3458 | 8800 | 0.6978 | 0.5337 |
100
- | 0.4774 | 0.3536 | 9000 | 0.6567 | 0.5211 |
101
- | 0.4774 | 0.3615 | 9200 | 0.6479 | 0.5152 |
102
- | 0.4774 | 0.3694 | 9400 | 0.6551 | 0.5147 |
103
- | 0.4632 | 0.3772 | 9600 | 0.6358 | 0.4955 |
104
- | 0.4632 | 0.3851 | 9800 | 0.6466 | 0.5109 |
105
- | 0.4483 | 0.3929 | 10000 | 0.6306 | 0.5044 |
106
- | 0.4483 | 0.4008 | 10200 | 0.6360 | 0.5004 |
107
- | 0.4483 | 0.4087 | 10400 | 0.6302 | 0.4914 |
108
- | 0.4454 | 0.4165 | 10600 | 0.6163 | 0.4851 |
109
- | 0.4454 | 0.4244 | 10800 | 0.6221 | 0.4911 |
110
- | 0.4302 | 0.4322 | 11000 | 0.6396 | 0.5001 |
111
- | 0.4302 | 0.4401 | 11200 | 0.6212 | 0.4841 |
112
- | 0.4302 | 0.4480 | 11400 | 0.6268 | 0.4938 |
113
- | 0.4261 | 0.4558 | 11600 | 0.6098 | 0.4820 |
114
- | 0.4261 | 0.4637 | 11800 | 0.6009 | 0.4689 |
115
- | 0.4026 | 0.4715 | 12000 | 0.6091 | 0.4810 |
116
- | 0.4026 | 0.4794 | 12200 | 0.6019 | 0.4806 |
117
- | 0.4026 | 0.4872 | 12400 | 0.5947 | 0.4671 |
118
- | 0.4027 | 0.4951 | 12600 | 0.5994 | 0.4709 |
119
- | 0.4027 | 0.5030 | 12800 | 0.5982 | 0.4761 |
120
- | 0.3978 | 0.5108 | 13000 | 0.5890 | 0.4632 |
121
- | 0.3978 | 0.5187 | 13200 | 0.5871 | 0.4567 |
122
- | 0.3978 | 0.5265 | 13400 | 0.5873 | 0.4635 |
123
- | 0.3875 | 0.5344 | 13600 | 0.5772 | 0.4539 |
124
- | 0.3875 | 0.5423 | 13800 | 0.5604 | 0.4419 |
125
- | 0.404 | 0.5501 | 14000 | 0.5689 | 0.4454 |
126
- | 0.404 | 0.5580 | 14200 | 0.5595 | 0.4433 |
127
- | 0.404 | 0.5658 | 14400 | 0.5575 | 0.4406 |
128
- | 0.3878 | 0.5737 | 14600 | 0.5522 | 0.4353 |
129
- | 0.3878 | 0.5816 | 14800 | 0.5522 | 0.4352 |
130
- | 0.3622 | 0.5894 | 15000 | 0.5570 | 0.4401 |
131
- | 0.3622 | 0.5973 | 15200 | 0.5467 | 0.4280 |
132
- | 0.3622 | 0.6051 | 15400 | 0.5511 | 0.4340 |
133
- | 0.3545 | 0.6130 | 15600 | 0.5437 | 0.4245 |
134
- | 0.3545 | 0.6208 | 15800 | 0.5489 | 0.4296 |
135
- | 0.3486 | 0.6287 | 16000 | 0.5420 | 0.4278 |
136
- | 0.3486 | 0.6366 | 16200 | 0.5352 | 0.4213 |
137
- | 0.3486 | 0.6444 | 16400 | 0.5377 | 0.4259 |
138
- | 0.3374 | 0.6523 | 16600 | 0.5336 | 0.4305 |
139
- | 0.3374 | 0.6601 | 16800 | 0.5294 | 0.4188 |
140
- | 0.3389 | 0.6680 | 17000 | 0.5253 | 0.4169 |
141
- | 0.3389 | 0.6759 | 17200 | 0.5194 | 0.4144 |
142
- | 0.3389 | 0.6837 | 17400 | 0.5232 | 0.4171 |
143
- | 0.3258 | 0.6916 | 17600 | 0.5179 | 0.4165 |
144
- | 0.3258 | 0.6994 | 17800 | 0.5132 | 0.4104 |
145
- | 0.327 | 0.7073 | 18000 | 0.5096 | 0.4044 |
146
- | 0.327 | 0.7152 | 18200 | 0.5041 | 0.4034 |
147
- | 0.327 | 0.7230 | 18400 | 0.5013 | 0.3981 |
148
- | 0.316 | 0.7309 | 18600 | 0.5074 | 0.4065 |
149
- | 0.316 | 0.7387 | 18800 | 0.5014 | 0.4055 |
150
- | 0.3162 | 0.7466 | 19000 | 0.4959 | 0.3998 |
151
- | 0.3162 | 0.7545 | 19200 | 0.4930 | 0.3982 |
152
- | 0.3162 | 0.7623 | 19400 | 0.4925 | 0.3982 |
153
- | 0.3145 | 0.7702 | 19600 | 0.4922 | 0.3970 |
154
- | 0.3145 | 0.7780 | 19800 | 0.4908 | 0.3969 |
155
- | 0.3095 | 0.7859 | 20000 | 0.4908 | 0.3964 |
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
156
 
157
 
158
  ### Framework versions
 
2
  license: apache-2.0
3
  base_model: facebook/wav2vec2-large-xlsr-53
4
  tags:
 
 
5
  - generated_from_trainer
6
  metrics:
7
  - wer
 
15
 
16
  # wav2vec2-xlsr-53-ft-btb-ccv-cy
17
 
18
+ This model is a fine-tuned version of [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on an unknown dataset.
19
  It achieves the following results on the evaluation set:
20
+ - Loss: 0.4511
21
+ - Wer: 0.3591
22
 
23
  ## Model description
24
 
 
44
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
45
  - lr_scheduler_type: linear
46
  - lr_scheduler_warmup_steps: 500
47
+ - training_steps: 30000
48
  - mixed_precision_training: Native AMP
49
 
50
  ### Training results
51
 
52
  | Training Loss | Epoch | Step | Validation Loss | Wer |
53
  |:-------------:|:------:|:-----:|:---------------:|:------:|
54
+ | No log | 0.0079 | 200 | 3.1893 | 1.0 |
55
+ | No log | 0.0157 | 400 | 2.7802 | 1.0 |
56
+ | 4.719 | 0.0236 | 600 | 1.4221 | 0.8877 |
57
+ | 4.719 | 0.0314 | 800 | 1.2274 | 0.8224 |
58
+ | 1.0441 | 0.0393 | 1000 | 1.1095 | 0.7887 |
59
+ | 1.0441 | 0.0472 | 1200 | 1.0914 | 0.7549 |
60
+ | 1.0441 | 0.0550 | 1400 | 1.0177 | 0.7355 |
61
+ | 0.8033 | 0.0629 | 1600 | 0.9907 | 0.7233 |
62
+ | 0.8033 | 0.0707 | 1800 | 0.9761 | 0.7145 |
63
+ | 0.7227 | 0.0786 | 2000 | 0.9555 | 0.6903 |
64
+ | 0.7227 | 0.0864 | 2200 | 0.8995 | 0.6748 |
65
+ | 0.7227 | 0.0943 | 2400 | 0.8897 | 0.6666 |
66
+ | 0.6794 | 0.1022 | 2600 | 0.8826 | 0.6560 |
67
+ | 0.6794 | 0.1100 | 2800 | 0.8745 | 0.6446 |
68
+ | 0.6513 | 0.1179 | 3000 | 0.8450 | 0.6437 |
69
+ | 0.6513 | 0.1257 | 3200 | 0.8596 | 0.6511 |
70
+ | 0.6513 | 0.1336 | 3400 | 0.8598 | 0.6376 |
71
+ | 0.6147 | 0.1415 | 3600 | 0.8516 | 0.6375 |
72
+ | 0.6147 | 0.1493 | 3800 | 0.8252 | 0.6100 |
73
+ | 0.6092 | 0.1572 | 4000 | 0.8580 | 0.6823 |
74
+ | 0.6092 | 0.1650 | 4200 | 0.8205 | 0.6136 |
75
+ | 0.6092 | 0.1729 | 4400 | 0.8033 | 0.6385 |
76
+ | 0.5928 | 0.1808 | 4600 | 0.7928 | 0.6005 |
77
+ | 0.5928 | 0.1886 | 4800 | 0.7911 | 0.5924 |
78
+ | 0.5681 | 0.1965 | 5000 | 0.7969 | 0.5944 |
79
+ | 0.5681 | 0.2043 | 5200 | 0.7933 | 0.5899 |
80
+ | 0.5681 | 0.2122 | 5400 | 0.7830 | 0.6013 |
81
+ | 0.5806 | 0.2200 | 5600 | 0.7703 | 0.5789 |
82
+ | 0.5806 | 0.2279 | 5800 | 0.7666 | 0.5898 |
83
+ | 0.5608 | 0.2358 | 6000 | 0.7580 | 0.5695 |
84
+ | 0.5608 | 0.2436 | 6200 | 0.7479 | 0.5651 |
85
+ | 0.5608 | 0.2515 | 6400 | 0.7639 | 0.5847 |
86
+ | 0.5333 | 0.2593 | 6600 | 0.7297 | 0.5676 |
87
+ | 0.5333 | 0.2672 | 6800 | 0.7441 | 0.5590 |
88
+ | 0.5406 | 0.2751 | 7000 | 0.7405 | 0.5491 |
89
+ | 0.5406 | 0.2829 | 7200 | 0.7238 | 0.5529 |
90
+ | 0.5406 | 0.2908 | 7400 | 0.7328 | 0.5544 |
91
+ | 0.535 | 0.2986 | 7600 | 0.7263 | 0.5599 |
92
+ | 0.535 | 0.3065 | 7800 | 0.7421 | 0.5594 |
93
+ | 0.5195 | 0.3144 | 8000 | 0.7435 | 0.5544 |
94
+ | 0.5195 | 0.3222 | 8200 | 0.7187 | 0.5424 |
95
+ | 0.5195 | 0.3301 | 8400 | 0.6977 | 0.5353 |
96
+ | 0.5023 | 0.3379 | 8600 | 0.6950 | 0.5386 |
97
+ | 0.5023 | 0.3458 | 8800 | 0.7155 | 0.5451 |
98
+ | 0.5106 | 0.3536 | 9000 | 0.6857 | 0.5379 |
99
+ | 0.5106 | 0.3615 | 9200 | 0.6848 | 0.5329 |
100
+ | 0.5106 | 0.3694 | 9400 | 0.6732 | 0.5202 |
101
+ | 0.4968 | 0.3772 | 9600 | 0.6839 | 0.5275 |
102
+ | 0.4968 | 0.3851 | 9800 | 0.6767 | 0.5198 |
103
+ | 0.4824 | 0.3929 | 10000 | 0.6718 | 0.5335 |
104
+ | 0.4824 | 0.4008 | 10200 | 0.6593 | 0.5175 |
105
+ | 0.4824 | 0.4087 | 10400 | 0.6799 | 0.5174 |
106
+ | 0.48 | 0.4165 | 10600 | 0.6662 | 0.5129 |
107
+ | 0.48 | 0.4244 | 10800 | 0.6619 | 0.5006 |
108
+ | 0.4693 | 0.4322 | 11000 | 0.6576 | 0.5199 |
109
+ | 0.4693 | 0.4401 | 11200 | 0.6406 | 0.5019 |
110
+ | 0.4693 | 0.4480 | 11400 | 0.6408 | 0.5066 |
111
+ | 0.4691 | 0.4558 | 11600 | 0.6476 | 0.5019 |
112
+ | 0.4691 | 0.4637 | 11800 | 0.6423 | 0.4946 |
113
+ | 0.4444 | 0.4715 | 12000 | 0.6374 | 0.4976 |
114
+ | 0.4444 | 0.4794 | 12200 | 0.6312 | 0.4961 |
115
+ | 0.4444 | 0.4872 | 12400 | 0.6170 | 0.4819 |
116
+ | 0.4474 | 0.4951 | 12600 | 0.6301 | 0.4933 |
117
+ | 0.4474 | 0.5030 | 12800 | 0.6253 | 0.4862 |
118
+ | 0.4471 | 0.5108 | 13000 | 0.6220 | 0.4849 |
119
+ | 0.4471 | 0.5187 | 13200 | 0.6201 | 0.4853 |
120
+ | 0.4471 | 0.5265 | 13400 | 0.6168 | 0.4848 |
121
+ | 0.4323 | 0.5344 | 13600 | 0.6173 | 0.4771 |
122
+ | 0.4323 | 0.5423 | 13800 | 0.6032 | 0.4656 |
123
+ | 0.4575 | 0.5501 | 14000 | 0.6097 | 0.4678 |
124
+ | 0.4575 | 0.5580 | 14200 | 0.5971 | 0.4674 |
125
+ | 0.4575 | 0.5658 | 14400 | 0.5977 | 0.4698 |
126
+ | 0.4395 | 0.5737 | 14600 | 0.6057 | 0.4734 |
127
+ | 0.4395 | 0.5816 | 14800 | 0.5827 | 0.4574 |
128
+ | 0.4119 | 0.5894 | 15000 | 0.5946 | 0.4640 |
129
+ | 0.4119 | 0.5973 | 15200 | 0.6023 | 0.4771 |
130
+ | 0.4119 | 0.6051 | 15400 | 0.6129 | 0.4727 |
131
+ | 0.4125 | 0.6130 | 15600 | 0.5902 | 0.4584 |
132
+ | 0.4125 | 0.6208 | 15800 | 0.5955 | 0.4654 |
133
+ | 0.4039 | 0.6287 | 16000 | 0.5955 | 0.4595 |
134
+ | 0.4039 | 0.6366 | 16200 | 0.5789 | 0.4497 |
135
+ | 0.4039 | 0.6444 | 16400 | 0.5779 | 0.4630 |
136
+ | 0.3969 | 0.6523 | 16600 | 0.5677 | 0.4551 |
137
+ | 0.3969 | 0.6601 | 16800 | 0.5869 | 0.4606 |
138
+ | 0.3923 | 0.6680 | 17000 | 0.5710 | 0.4502 |
139
+ | 0.3923 | 0.6759 | 17200 | 0.5640 | 0.4474 |
140
+ | 0.3923 | 0.6837 | 17400 | 0.5842 | 0.4498 |
141
+ | 0.386 | 0.6916 | 17600 | 0.5597 | 0.4440 |
142
+ | 0.386 | 0.6994 | 17800 | 0.5621 | 0.4381 |
143
+ | 0.3851 | 0.7073 | 18000 | 0.5665 | 0.4346 |
144
+ | 0.3851 | 0.7152 | 18200 | 0.5573 | 0.4356 |
145
+ | 0.3851 | 0.7230 | 18400 | 0.5548 | 0.4344 |
146
+ | 0.369 | 0.7309 | 18600 | 0.5617 | 0.4364 |
147
+ | 0.369 | 0.7387 | 18800 | 0.5596 | 0.4394 |
148
+ | 0.3738 | 0.7466 | 19000 | 0.5492 | 0.4292 |
149
+ | 0.3738 | 0.7545 | 19200 | 0.5478 | 0.4372 |
150
+ | 0.3738 | 0.7623 | 19400 | 0.5376 | 0.4287 |
151
+ | 0.368 | 0.7702 | 19600 | 0.5282 | 0.4193 |
152
+ | 0.368 | 0.7780 | 19800 | 0.5348 | 0.4251 |
153
+ | 0.3629 | 0.7859 | 20000 | 0.5368 | 0.4313 |
154
+ | 0.3629 | 0.7937 | 20200 | 0.5551 | 0.4412 |
155
+ | 0.3629 | 0.8016 | 20400 | 0.5252 | 0.4105 |
156
+ | 0.3638 | 0.8095 | 20600 | 0.5242 | 0.4117 |
157
+ | 0.3638 | 0.8173 | 20800 | 0.5233 | 0.4166 |
158
+ | 0.3512 | 0.8252 | 21000 | 0.5243 | 0.4161 |
159
+ | 0.3512 | 0.8330 | 21200 | 0.5150 | 0.4123 |
160
+ | 0.3512 | 0.8409 | 21400 | 0.5089 | 0.4080 |
161
+ | 0.3536 | 0.8488 | 21600 | 0.5154 | 0.4090 |
162
+ | 0.3536 | 0.8566 | 21800 | 0.5162 | 0.4092 |
163
+ | 0.3464 | 0.8645 | 22000 | 0.5098 | 0.4053 |
164
+ | 0.3464 | 0.8723 | 22200 | 0.5070 | 0.4023 |
165
+ | 0.3464 | 0.8802 | 22400 | 0.5070 | 0.4071 |
166
+ | 0.3377 | 0.8881 | 22600 | 0.5028 | 0.3967 |
167
+ | 0.3377 | 0.8959 | 22800 | 0.5036 | 0.3978 |
168
+ | 0.3272 | 0.9038 | 23000 | 0.5021 | 0.3954 |
169
+ | 0.3272 | 0.9116 | 23200 | 0.5033 | 0.3985 |
170
+ | 0.3272 | 0.9195 | 23400 | 0.4984 | 0.3972 |
171
+ | 0.319 | 0.9273 | 23600 | 0.4929 | 0.3924 |
172
+ | 0.319 | 0.9352 | 23800 | 0.4941 | 0.4013 |
173
+ | 0.3184 | 0.9431 | 24000 | 0.4856 | 0.3874 |
174
+ | 0.3184 | 0.9509 | 24200 | 0.4892 | 0.3914 |
175
+ | 0.3184 | 0.9588 | 24400 | 0.4860 | 0.3814 |
176
+ | 0.3091 | 0.9666 | 24600 | 0.4825 | 0.3834 |
177
+ | 0.3091 | 0.9745 | 24800 | 0.4784 | 0.3867 |
178
+ | 0.3154 | 0.9824 | 25000 | 0.4751 | 0.3808 |
179
+ | 0.3154 | 0.9902 | 25200 | 0.4779 | 0.3849 |
180
+ | 0.3154 | 0.9981 | 25400 | 0.4773 | 0.3808 |
181
+ | 0.312 | 1.0059 | 25600 | 0.4777 | 0.3758 |
182
+ | 0.312 | 1.0138 | 25800 | 0.4752 | 0.3821 |
183
+ | 0.2651 | 1.0217 | 26000 | 0.4701 | 0.3775 |
184
+ | 0.2651 | 1.0295 | 26200 | 0.4701 | 0.3761 |
185
+ | 0.2651 | 1.0374 | 26400 | 0.4718 | 0.3776 |
186
+ | 0.2627 | 1.0452 | 26600 | 0.4638 | 0.3730 |
187
+ | 0.2627 | 1.0531 | 26800 | 0.4677 | 0.3720 |
188
+ | 0.2427 | 1.0609 | 27000 | 0.4643 | 0.3699 |
189
+ | 0.2427 | 1.0688 | 27200 | 0.4602 | 0.3713 |
190
+ | 0.2427 | 1.0767 | 27400 | 0.4664 | 0.3703 |
191
+ | 0.2464 | 1.0845 | 27600 | 0.4609 | 0.3677 |
192
+ | 0.2464 | 1.0924 | 27800 | 0.4614 | 0.3687 |
193
+ | 0.2537 | 1.1002 | 28000 | 0.4555 | 0.3655 |
194
+ | 0.2537 | 1.1081 | 28200 | 0.4560 | 0.3645 |
195
+ | 0.2537 | 1.1160 | 28400 | 0.4543 | 0.3626 |
196
+ | 0.2313 | 1.1238 | 28600 | 0.4540 | 0.3631 |
197
+ | 0.2313 | 1.1317 | 28800 | 0.4536 | 0.3626 |
198
+ | 0.2451 | 1.1395 | 29000 | 0.4529 | 0.3617 |
199
+ | 0.2451 | 1.1474 | 29200 | 0.4530 | 0.3598 |
200
+ | 0.2451 | 1.1553 | 29400 | 0.4515 | 0.3592 |
201
+ | 0.2445 | 1.1631 | 29600 | 0.4514 | 0.3590 |
202
+ | 0.2445 | 1.1710 | 29800 | 0.4514 | 0.3589 |
203
+ | 0.2364 | 1.1788 | 30000 | 0.4511 | 0.3591 |
204
 
205
 
206
  ### Framework versions