End of training
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README.md
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---
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license: apache-2.0
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tags:
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- generated_from_trainer
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model-index:
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@@ -14,8 +15,8 @@ should probably proofread and complete it, then remove this comment. -->
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This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.
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- Cer: 0.
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## Model description
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@@ -48,248 +49,248 @@ The following hyperparameters were used during training:
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| Training Loss | Epoch | Step | Validation Loss | Cer |
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|:-------------:|:-----:|:------:|:---------------:|:------:|
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### Framework versions
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-
- Transformers 4.
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-
- Pytorch 2.
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- Datasets 2.13.0
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-
- Tokenizers 0.
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|
| 1 |
---
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license: apache-2.0
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| 3 |
+
base_model: facebook/wav2vec2-xls-r-300m
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| 4 |
tags:
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| 5 |
- generated_from_trainer
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model-index:
|
|
|
|
| 15 |
|
| 16 |
This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the None dataset.
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| 17 |
It achieves the following results on the evaluation set:
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+
- Loss: 0.0074
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| 19 |
+
- Cer: 0.0011
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| 20 |
|
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## Model description
|
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|
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| 49 |
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| Training Loss | Epoch | Step | Validation Loss | Cer |
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|:-------------:|:-----:|:------:|:---------------:|:------:|
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| 9.6728 | 0.08 | 500 | 0.9218 | 1.0 |
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| 0.6369 | 0.17 | 1000 | 0.6685 | 1.0 |
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| 0.511 | 0.25 | 1500 | 0.4867 | 0.5464 |
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| 0.4632 | 0.34 | 2000 | 0.4821 | 0.2281 |
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| 0.4354 | 0.42 | 2500 | 0.3887 | 0.1763 |
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| 0.3664 | 0.51 | 3000 | 0.2324 | 0.0484 |
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| 0.2641 | 0.59 | 3500 | 0.1729 | 0.0276 |
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| 0.218 | 0.67 | 4000 | 0.1485 | 0.0213 |
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| 0.1938 | 0.76 | 4500 | 0.1270 | 0.0188 |
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| 0.1867 | 0.84 | 5000 | 0.1192 | 0.0177 |
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| 0.1756 | 0.93 | 5500 | 0.1047 | 0.0163 |
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| 0.1659 | 1.01 | 6000 | 0.1008 | 0.0150 |
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| 0.1522 | 1.1 | 6500 | 0.0970 | 0.0140 |
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| 0.1456 | 1.18 | 7000 | 0.0944 | 0.0140 |
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| 0.1431 | 1.26 | 7500 | 0.0905 | 0.0134 |
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| 0.1416 | 1.35 | 8000 | 0.0919 | 0.0120 |
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| 0.1356 | 1.43 | 8500 | 0.0792 | 0.0124 |
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| 0.1345 | 1.52 | 9000 | 0.0880 | 0.0129 |
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| 0.1316 | 1.6 | 9500 | 0.0753 | 0.0111 |
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| 0.1293 | 1.69 | 10000 | 0.0728 | 0.0106 |
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| 0.1238 | 1.77 | 10500 | 0.0682 | 0.0109 |
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| 0.121 | 1.85 | 11000 | 0.0645 | 0.0100 |
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| 0.1161 | 1.94 | 11500 | 0.0658 | 0.0094 |
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| 0.1107 | 2.02 | 12000 | 0.0669 | 0.0115 |
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| 0.1054 | 2.11 | 12500 | 0.0597 | 0.0093 |
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| 0.104 | 2.19 | 13000 | 0.0572 | 0.0088 |
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| 0.1007 | 2.28 | 13500 | 0.0522 | 0.0082 |
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| 0.0986 | 2.36 | 14000 | 0.0575 | 0.0090 |
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| 0.103 | 2.44 | 14500 | 0.0513 | 0.0085 |
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| 0.0973 | 2.53 | 15000 | 0.0597 | 0.0081 |
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| 0.0949 | 2.61 | 15500 | 0.0474 | 0.0074 |
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| 0.092 | 2.7 | 16000 | 0.0538 | 0.0083 |
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| 0.0944 | 2.78 | 16500 | 0.0471 | 0.0078 |
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| 0.0896 | 2.87 | 17000 | 0.0417 | 0.0064 |
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| 0.0895 | 2.95 | 17500 | 0.0406 | 0.0063 |
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| 0.0866 | 3.03 | 18000 | 0.0393 | 0.0064 |
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| 0.0795 | 3.12 | 18500 | 0.0377 | 0.0067 |
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| 0.0803 | 3.2 | 19000 | 0.0380 | 0.0063 |
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| 0.0771 | 3.29 | 19500 | 0.0386 | 0.0058 |
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| 0.0742 | 3.37 | 20000 | 0.0347 | 0.0057 |
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| 0.0743 | 3.46 | 20500 | 0.0363 | 0.0062 |
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| 0.073 | 3.54 | 21000 | 0.0314 | 0.0051 |
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| 0.0727 | 3.62 | 21500 | 0.0293 | 0.0050 |
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| 0.0693 | 3.71 | 22000 | 0.0331 | 0.0057 |
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| 0.0689 | 3.79 | 22500 | 0.0306 | 0.0050 |
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| 0.0712 | 3.88 | 23000 | 0.0304 | 0.0049 |
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| 0.0697 | 3.96 | 23500 | 0.0287 | 0.0050 |
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| 0.0656 | 4.05 | 24000 | 0.0269 | 0.0046 |
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| 0.0624 | 4.13 | 24500 | 0.0282 | 0.0048 |
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| 0.0614 | 4.21 | 25000 | 0.0262 | 0.0046 |
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| 0.0589 | 4.3 | 25500 | 0.0245 | 0.0044 |
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| 0.0596 | 4.38 | 26000 | 0.0237 | 0.0043 |
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| 0.0589 | 4.47 | 26500 | 0.0233 | 0.0045 |
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| 0.059 | 4.55 | 27000 | 0.0275 | 0.0044 |
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| 0.0564 | 4.64 | 27500 | 0.0241 | 0.0042 |
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| 0.0589 | 4.72 | 28000 | 0.0209 | 0.0044 |
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| 108 |
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| 0.055 | 4.8 | 28500 | 0.0199 | 0.0039 |
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| 0.0629 | 4.89 | 29000 | 0.0223 | 0.0046 |
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| 0.0581 | 4.97 | 29500 | 0.0234 | 0.0044 |
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| 0.0529 | 5.06 | 30000 | 0.0197 | 0.0037 |
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| 0.0489 | 5.14 | 30500 | 0.0232 | 0.0044 |
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| 0.0512 | 5.23 | 31000 | 0.0202 | 0.0039 |
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| 0.0501 | 5.31 | 31500 | 0.0182 | 0.0036 |
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| 115 |
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| 0.0494 | 5.39 | 32000 | 0.0181 | 0.0034 |
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| 0.049 | 5.48 | 32500 | 0.0173 | 0.0034 |
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| 0.0482 | 5.56 | 33000 | 0.0173 | 0.0034 |
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| 0.0505 | 5.65 | 33500 | 0.0172 | 0.0033 |
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| 0.048 | 5.73 | 34000 | 0.0168 | 0.0034 |
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| 0.0485 | 5.82 | 34500 | 0.0162 | 0.0032 |
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| 0.0461 | 5.9 | 35000 | 0.0154 | 0.0032 |
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| 0.0436 | 5.98 | 35500 | 0.0152 | 0.0033 |
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| 0.043 | 6.07 | 36000 | 0.0157 | 0.0033 |
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| 0.0429 | 6.15 | 36500 | 0.0160 | 0.0036 |
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| 0.0402 | 6.24 | 37000 | 0.0169 | 0.0034 |
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| 0.043 | 6.32 | 37500 | 0.0135 | 0.0030 |
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| 0.0409 | 6.41 | 38000 | 0.0167 | 0.0033 |
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| 0.0446 | 6.49 | 38500 | 0.0155 | 0.0035 |
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| 0.0402 | 6.57 | 39000 | 0.0145 | 0.0029 |
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| 0.0427 | 6.66 | 39500 | 0.0139 | 0.0028 |
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| 0.0392 | 6.74 | 40000 | 0.0148 | 0.0028 |
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| 0.0395 | 6.83 | 40500 | 0.0144 | 0.0026 |
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| 0.0396 | 6.91 | 41000 | 0.0208 | 0.0035 |
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| 0.0394 | 7.0 | 41500 | 0.0127 | 0.0026 |
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| 0.0367 | 7.08 | 42000 | 0.0129 | 0.0023 |
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| 0.0368 | 7.16 | 42500 | 0.0120 | 0.0024 |
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| 0.0345 | 7.25 | 43000 | 0.0119 | 0.0027 |
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| 0.0342 | 7.33 | 43500 | 0.0123 | 0.0026 |
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| 0.0368 | 7.42 | 44000 | 0.0109 | 0.0024 |
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| 0.0358 | 7.5 | 44500 | 0.0120 | 0.0026 |
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| 0.036 | 7.59 | 45000 | 0.0110 | 0.0026 |
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| 0.0332 | 7.67 | 45500 | 0.0115 | 0.0024 |
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| 0.0356 | 7.75 | 46000 | 0.0128 | 0.0024 |
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| 0.0353 | 7.84 | 46500 | 0.0123 | 0.0024 |
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| 0.0365 | 7.92 | 47000 | 0.0106 | 0.0023 |
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| 146 |
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| 0.0341 | 8.01 | 47500 | 0.0110 | 0.0023 |
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| 147 |
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| 0.0286 | 8.09 | 48000 | 0.0109 | 0.0023 |
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| 148 |
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| 0.0324 | 8.18 | 48500 | 0.0099 | 0.0022 |
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| 0.0321 | 8.26 | 49000 | 0.0111 | 0.0023 |
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| 0.0333 | 8.34 | 49500 | 0.0110 | 0.0023 |
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| 0.0302 | 8.43 | 50000 | 0.0116 | 0.0026 |
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| 152 |
+
| 0.0325 | 8.51 | 50500 | 0.0123 | 0.0025 |
|
| 153 |
+
| 0.0317 | 8.6 | 51000 | 0.0101 | 0.0027 |
|
| 154 |
+
| 0.032 | 8.68 | 51500 | 0.0108 | 0.0024 |
|
| 155 |
+
| 0.0298 | 8.77 | 52000 | 0.0105 | 0.0024 |
|
| 156 |
+
| 0.0304 | 8.85 | 52500 | 0.0113 | 0.0022 |
|
| 157 |
+
| 0.0315 | 8.93 | 53000 | 0.0109 | 0.0023 |
|
| 158 |
+
| 0.0299 | 9.02 | 53500 | 0.0102 | 0.0022 |
|
| 159 |
+
| 0.029 | 9.1 | 54000 | 0.0108 | 0.0021 |
|
| 160 |
+
| 0.0261 | 9.19 | 54500 | 0.0112 | 0.0022 |
|
| 161 |
+
| 0.0286 | 9.27 | 55000 | 0.0116 | 0.0023 |
|
| 162 |
+
| 0.0293 | 9.36 | 55500 | 0.0108 | 0.0023 |
|
| 163 |
+
| 0.0267 | 9.44 | 56000 | 0.0109 | 0.0023 |
|
| 164 |
+
| 0.0271 | 9.52 | 56500 | 0.0103 | 0.0021 |
|
| 165 |
+
| 0.0276 | 9.61 | 57000 | 0.0102 | 0.0021 |
|
| 166 |
+
| 0.0256 | 9.69 | 57500 | 0.0101 | 0.0021 |
|
| 167 |
+
| 0.0264 | 9.78 | 58000 | 0.0131 | 0.0021 |
|
| 168 |
+
| 0.0277 | 9.86 | 58500 | 0.0096 | 0.0021 |
|
| 169 |
+
| 0.0303 | 9.95 | 59000 | 0.0097 | 0.0020 |
|
| 170 |
+
| 0.027 | 10.03 | 59500 | 0.0102 | 0.0021 |
|
| 171 |
+
| 0.0241 | 10.11 | 60000 | 0.0089 | 0.0020 |
|
| 172 |
+
| 0.0226 | 10.2 | 60500 | 0.0108 | 0.0020 |
|
| 173 |
+
| 0.0248 | 10.28 | 61000 | 0.0109 | 0.0021 |
|
| 174 |
+
| 0.0244 | 10.37 | 61500 | 0.0093 | 0.0020 |
|
| 175 |
+
| 0.025 | 10.45 | 62000 | 0.0167 | 0.0021 |
|
| 176 |
+
| 0.0238 | 10.54 | 62500 | 0.0123 | 0.0019 |
|
| 177 |
+
| 0.0253 | 10.62 | 63000 | 0.0089 | 0.0019 |
|
| 178 |
+
| 0.0247 | 10.7 | 63500 | 0.0090 | 0.0019 |
|
| 179 |
+
| 0.0229 | 10.79 | 64000 | 0.0084 | 0.0017 |
|
| 180 |
+
| 0.0242 | 10.87 | 64500 | 0.0086 | 0.0019 |
|
| 181 |
+
| 0.0251 | 10.96 | 65000 | 0.0082 | 0.0017 |
|
| 182 |
+
| 0.0222 | 11.04 | 65500 | 0.0081 | 0.0017 |
|
| 183 |
+
| 0.0233 | 11.13 | 66000 | 0.0078 | 0.0018 |
|
| 184 |
+
| 0.0226 | 11.21 | 66500 | 0.0081 | 0.0017 |
|
| 185 |
+
| 0.0227 | 11.29 | 67000 | 0.0096 | 0.0018 |
|
| 186 |
+
| 0.024 | 11.38 | 67500 | 0.0081 | 0.0017 |
|
| 187 |
+
| 0.0217 | 11.46 | 68000 | 0.0088 | 0.0019 |
|
| 188 |
+
| 0.0222 | 11.55 | 68500 | 0.0086 | 0.0019 |
|
| 189 |
+
| 0.0229 | 11.63 | 69000 | 0.0091 | 0.0021 |
|
| 190 |
+
| 0.02 | 11.72 | 69500 | 0.0094 | 0.0020 |
|
| 191 |
+
| 0.022 | 11.8 | 70000 | 0.0095 | 0.0017 |
|
| 192 |
+
| 0.0232 | 11.88 | 70500 | 0.0078 | 0.0018 |
|
| 193 |
+
| 0.0216 | 11.97 | 71000 | 0.0088 | 0.0017 |
|
| 194 |
+
| 0.0216 | 12.05 | 71500 | 0.0081 | 0.0017 |
|
| 195 |
+
| 0.0182 | 12.14 | 72000 | 0.0088 | 0.0018 |
|
| 196 |
+
| 0.0196 | 12.22 | 72500 | 0.0092 | 0.0017 |
|
| 197 |
+
| 0.0203 | 12.31 | 73000 | 0.0083 | 0.0018 |
|
| 198 |
+
| 0.0191 | 12.39 | 73500 | 0.0086 | 0.0018 |
|
| 199 |
+
| 0.0192 | 12.47 | 74000 | 0.0122 | 0.0016 |
|
| 200 |
+
| 0.0194 | 12.56 | 74500 | 0.0084 | 0.0016 |
|
| 201 |
+
| 0.0192 | 12.64 | 75000 | 0.0098 | 0.0016 |
|
| 202 |
+
| 0.0192 | 12.73 | 75500 | 0.0101 | 0.0017 |
|
| 203 |
+
| 0.0191 | 12.81 | 76000 | 0.0100 | 0.0016 |
|
| 204 |
+
| 0.0191 | 12.9 | 76500 | 0.0091 | 0.0016 |
|
| 205 |
+
| 0.0184 | 12.98 | 77000 | 0.0084 | 0.0017 |
|
| 206 |
+
| 0.0188 | 13.06 | 77500 | 0.0080 | 0.0016 |
|
| 207 |
+
| 0.0188 | 13.15 | 78000 | 0.0094 | 0.0017 |
|
| 208 |
+
| 0.0172 | 13.23 | 78500 | 0.0098 | 0.0017 |
|
| 209 |
+
| 0.0174 | 13.32 | 79000 | 0.0134 | 0.0015 |
|
| 210 |
+
| 0.0177 | 13.4 | 79500 | 0.0106 | 0.0016 |
|
| 211 |
+
| 0.0178 | 13.49 | 80000 | 0.0100 | 0.0014 |
|
| 212 |
+
| 0.017 | 13.57 | 80500 | 0.0104 | 0.0016 |
|
| 213 |
+
| 0.0169 | 13.65 | 81000 | 0.0094 | 0.0014 |
|
| 214 |
+
| 0.0189 | 13.74 | 81500 | 0.0089 | 0.0015 |
|
| 215 |
+
| 0.0172 | 13.82 | 82000 | 0.0086 | 0.0016 |
|
| 216 |
+
| 0.0167 | 13.91 | 82500 | 0.0091 | 0.0015 |
|
| 217 |
+
| 0.0179 | 13.99 | 83000 | 0.0088 | 0.0015 |
|
| 218 |
+
| 0.0175 | 14.08 | 83500 | 0.0076 | 0.0014 |
|
| 219 |
+
| 0.0164 | 14.16 | 84000 | 0.0082 | 0.0013 |
|
| 220 |
+
| 0.0143 | 14.24 | 84500 | 0.0080 | 0.0015 |
|
| 221 |
+
| 0.0158 | 14.33 | 85000 | 0.0082 | 0.0014 |
|
| 222 |
+
| 0.0153 | 14.41 | 85500 | 0.0086 | 0.0016 |
|
| 223 |
+
| 0.0173 | 14.5 | 86000 | 0.0077 | 0.0015 |
|
| 224 |
+
| 0.0149 | 14.58 | 86500 | 0.0084 | 0.0016 |
|
| 225 |
+
| 0.0153 | 14.67 | 87000 | 0.0078 | 0.0015 |
|
| 226 |
+
| 0.0157 | 14.75 | 87500 | 0.0074 | 0.0014 |
|
| 227 |
+
| 0.0173 | 14.83 | 88000 | 0.0086 | 0.0015 |
|
| 228 |
+
| 0.0171 | 14.92 | 88500 | 0.0080 | 0.0014 |
|
| 229 |
+
| 0.0148 | 15.0 | 89000 | 0.0073 | 0.0013 |
|
| 230 |
+
| 0.0145 | 15.09 | 89500 | 0.0074 | 0.0014 |
|
| 231 |
+
| 0.0153 | 15.17 | 90000 | 0.0068 | 0.0014 |
|
| 232 |
+
| 0.0156 | 15.26 | 90500 | 0.0070 | 0.0014 |
|
| 233 |
+
| 0.0143 | 15.34 | 91000 | 0.0072 | 0.0014 |
|
| 234 |
+
| 0.0143 | 15.42 | 91500 | 0.0069 | 0.0015 |
|
| 235 |
+
| 0.0139 | 15.51 | 92000 | 0.0070 | 0.0014 |
|
| 236 |
+
| 0.0149 | 15.59 | 92500 | 0.0087 | 0.0015 |
|
| 237 |
+
| 0.0124 | 15.68 | 93000 | 0.0074 | 0.0013 |
|
| 238 |
+
| 0.0139 | 15.76 | 93500 | 0.0076 | 0.0013 |
|
| 239 |
+
| 0.0148 | 15.85 | 94000 | 0.0074 | 0.0014 |
|
| 240 |
+
| 0.013 | 15.93 | 94500 | 0.0073 | 0.0014 |
|
| 241 |
+
| 0.0138 | 16.01 | 95000 | 0.0069 | 0.0013 |
|
| 242 |
+
| 0.0148 | 16.1 | 95500 | 0.0069 | 0.0013 |
|
| 243 |
+
| 0.0135 | 16.18 | 96000 | 0.0067 | 0.0014 |
|
| 244 |
+
| 0.0143 | 16.27 | 96500 | 0.0067 | 0.0012 |
|
| 245 |
+
| 0.014 | 16.35 | 97000 | 0.0071 | 0.0013 |
|
| 246 |
+
| 0.0138 | 16.44 | 97500 | 0.0072 | 0.0012 |
|
| 247 |
+
| 0.0132 | 16.52 | 98000 | 0.0070 | 0.0012 |
|
| 248 |
+
| 0.0122 | 16.6 | 98500 | 0.0077 | 0.0013 |
|
| 249 |
+
| 0.0124 | 16.69 | 99000 | 0.0078 | 0.0013 |
|
| 250 |
+
| 0.0138 | 16.77 | 99500 | 0.0070 | 0.0012 |
|
| 251 |
+
| 0.0118 | 16.86 | 100000 | 0.0071 | 0.0013 |
|
| 252 |
+
| 0.0123 | 16.94 | 100500 | 0.0068 | 0.0013 |
|
| 253 |
+
| 0.0113 | 17.03 | 101000 | 0.0070 | 0.0013 |
|
| 254 |
+
| 0.011 | 17.11 | 101500 | 0.0076 | 0.0013 |
|
| 255 |
+
| 0.0117 | 17.19 | 102000 | 0.0073 | 0.0013 |
|
| 256 |
+
| 0.0123 | 17.28 | 102500 | 0.0078 | 0.0012 |
|
| 257 |
+
| 0.0132 | 17.36 | 103000 | 0.0072 | 0.0013 |
|
| 258 |
+
| 0.0105 | 17.45 | 103500 | 0.0078 | 0.0012 |
|
| 259 |
+
| 0.0115 | 17.53 | 104000 | 0.0078 | 0.0012 |
|
| 260 |
+
| 0.0112 | 17.62 | 104500 | 0.0076 | 0.0012 |
|
| 261 |
+
| 0.0108 | 17.7 | 105000 | 0.0080 | 0.0012 |
|
| 262 |
+
| 0.0106 | 17.78 | 105500 | 0.0080 | 0.0012 |
|
| 263 |
+
| 0.0114 | 17.87 | 106000 | 0.0074 | 0.0012 |
|
| 264 |
+
| 0.0127 | 17.95 | 106500 | 0.0070 | 0.0012 |
|
| 265 |
+
| 0.0105 | 18.04 | 107000 | 0.0073 | 0.0012 |
|
| 266 |
+
| 0.0108 | 18.12 | 107500 | 0.0083 | 0.0012 |
|
| 267 |
+
| 0.0107 | 18.21 | 108000 | 0.0088 | 0.0012 |
|
| 268 |
+
| 0.0102 | 18.29 | 108500 | 0.0080 | 0.0011 |
|
| 269 |
+
| 0.0089 | 18.37 | 109000 | 0.0073 | 0.0011 |
|
| 270 |
+
| 0.0107 | 18.46 | 109500 | 0.0073 | 0.0011 |
|
| 271 |
+
| 0.0112 | 18.54 | 110000 | 0.0078 | 0.0011 |
|
| 272 |
+
| 0.0106 | 18.63 | 110500 | 0.0077 | 0.0011 |
|
| 273 |
+
| 0.0101 | 18.71 | 111000 | 0.0078 | 0.0011 |
|
| 274 |
+
| 0.0111 | 18.8 | 111500 | 0.0080 | 0.0011 |
|
| 275 |
+
| 0.0106 | 18.88 | 112000 | 0.0073 | 0.0011 |
|
| 276 |
+
| 0.0102 | 18.96 | 112500 | 0.0075 | 0.0011 |
|
| 277 |
+
| 0.0098 | 19.05 | 113000 | 0.0075 | 0.0011 |
|
| 278 |
+
| 0.0118 | 19.13 | 113500 | 0.0078 | 0.0011 |
|
| 279 |
+
| 0.0094 | 19.22 | 114000 | 0.0077 | 0.0011 |
|
| 280 |
+
| 0.009 | 19.3 | 114500 | 0.0077 | 0.0011 |
|
| 281 |
+
| 0.0094 | 19.39 | 115000 | 0.0077 | 0.0011 |
|
| 282 |
+
| 0.0084 | 19.47 | 115500 | 0.0074 | 0.0010 |
|
| 283 |
+
| 0.011 | 19.55 | 116000 | 0.0076 | 0.0011 |
|
| 284 |
+
| 0.0106 | 19.64 | 116500 | 0.0073 | 0.0011 |
|
| 285 |
+
| 0.009 | 19.72 | 117000 | 0.0074 | 0.0011 |
|
| 286 |
+
| 0.0097 | 19.81 | 117500 | 0.0074 | 0.0011 |
|
| 287 |
+
| 0.0095 | 19.89 | 118000 | 0.0074 | 0.0011 |
|
| 288 |
+
| 0.0094 | 19.98 | 118500 | 0.0074 | 0.0011 |
|
| 289 |
|
| 290 |
|
| 291 |
### Framework versions
|
| 292 |
|
| 293 |
+
- Transformers 4.35.2
|
| 294 |
+
- Pytorch 2.1.1+cu121
|
| 295 |
- Datasets 2.13.0
|
| 296 |
+
- Tokenizers 0.15.0
|
model.safetensors
CHANGED
|
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size 1262020680
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runs/Jan04_15-05-44_DESKTOP-CE5K89C/events.out.tfevents.1704350035.DESKTOP-CE5K89C.15664.0
CHANGED
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