davanstrien / clip-roberta-finetuned

huggingface.co
Total runs: 87
24-hour runs: 2
7-day runs: -5
30-day runs: -527
Model's Last Updated: July 16 2022
feature-extraction

Introduction of clip-roberta-finetuned

Model Details of clip-roberta-finetuned

clip-roberta-finetuned

This model is a fine-tuned version of ./clip-roberta on the davanstrien/manuscript_noisy_labels_iiif dataset. It achieves the following results on the evaluation set:

  • Loss: 2.5792
Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure
Training hyperparameters

The following hyperparameters were used during training:

  • learning_rate: 5e-05
  • train_batch_size: 128
  • eval_batch_size: 256
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 10.0
  • mixed_precision_training: Native AMP
Training results
Training Loss Epoch Step Validation Loss
2.9841 0.07 500 3.4112
2.72 0.15 1000 3.3430
2.6319 0.22 1500 3.2295
2.5781 0.29 2000 3.1645
2.5339 0.36 2500 3.1226
2.503 0.44 3000 3.0856
2.4581 0.51 3500 3.0639
2.4494 0.58 4000 3.0415
2.4275 0.65 4500 3.0245
2.3909 0.73 5000 2.9991
2.3902 0.8 5500 2.9931
2.3741 0.87 6000 2.9612
2.3536 0.95 6500 2.9509
2.3392 1.02 7000 2.9289
2.3083 1.09 7500 2.9214
2.3094 1.16 8000 2.9153
2.2864 1.24 8500 2.9034
2.2893 1.31 9000 2.8963
2.2697 1.38 9500 2.8847
2.2762 1.46 10000 2.8665
2.2667 1.53 10500 2.8536
2.2548 1.6 11000 2.8472
2.238 1.67 11500 2.8491
2.2423 1.75 12000 2.8257
2.2406 1.82 12500 2.8287
2.2248 1.89 13000 2.8193
2.223 1.96 13500 2.8101
2.1995 2.04 14000 2.8027
2.1834 2.11 14500 2.7880
2.1723 2.18 15000 2.7783
2.1651 2.26 15500 2.7739
2.1575 2.33 16000 2.7825
2.1598 2.4 16500 2.7660
2.1667 2.47 17000 2.7578
2.1565 2.55 17500 2.7580
2.1558 2.62 18000 2.7561
2.1642 2.69 18500 2.7512
2.1374 2.77 19000 2.7361
2.1402 2.84 19500 2.7385
2.1326 2.91 20000 2.7235
2.1272 2.98 20500 2.7183
2.0954 3.06 21000 2.7156
2.0842 3.13 21500 2.7065
2.0859 3.2 22000 2.7089
2.0856 3.27 22500 2.6962
2.0775 3.35 23000 2.6931
2.0821 3.42 23500 2.6933
2.0706 3.49 24000 2.7011
2.0689 3.57 24500 2.7009
2.0807 3.64 25000 2.6825
2.0639 3.71 25500 2.6744
2.0742 3.78 26000 2.6777
2.0789 3.86 26500 2.6689
2.0594 3.93 27000 2.6566
2.056 4.0 27500 2.6676
2.0223 4.08 28000 2.6711
2.0185 4.15 28500 2.6568
2.018 4.22 29000 2.6567
2.0036 4.29 29500 2.6545
2.0238 4.37 30000 2.6559
2.0091 4.44 30500 2.6450
2.0096 4.51 31000 2.6389
2.0083 4.58 31500 2.6401
2.0012 4.66 32000 2.6399
2.0166 4.73 32500 2.6289
1.9963 4.8 33000 2.6348
1.9943 4.88 33500 2.6240
2.0099 4.95 34000 2.6190
1.9895 5.02 34500 2.6308
1.9581 5.09 35000 2.6385
1.9502 5.17 35500 2.6237
1.9485 5.24 36000 2.6248
1.9643 5.31 36500 2.6279
1.9535 5.38 37000 2.6185
1.9575 5.46 37500 2.6146
1.9475 5.53 38000 2.6093
1.9434 5.6 38500 2.6090
1.954 5.68 39000 2.6027
1.9509 5.75 39500 2.6107
1.9454 5.82 40000 2.5980
1.9479 5.89 40500 2.6016
1.9539 5.97 41000 2.5971
1.9119 6.04 41500 2.6228
1.8974 6.11 42000 2.6169
1.9038 6.19 42500 2.6027
1.9008 6.26 43000 2.6027
1.9142 6.33 43500 2.6011
1.8783 6.4 44000 2.5960
1.8896 6.48 44500 2.6111
1.8975 6.55 45000 2.5889
1.9048 6.62 45500 2.6007
1.9049 6.69 46000 2.5972
1.8969 6.77 46500 2.6053
1.9105 6.84 47000 2.5893
1.8921 6.91 47500 2.5883
1.8918 6.99 48000 2.5792
1.8671 7.06 48500 2.6041
1.8551 7.13 49000 2.6070
1.8555 7.2 49500 2.6148
1.8543 7.28 50000 2.6077
1.8485 7.35 50500 2.6131
1.8474 7.42 51000 2.6039
1.8474 7.5 51500 2.5973
1.8442 7.57 52000 2.5946
1.8329 7.64 52500 2.6069
1.8551 7.71 53000 2.5923
1.8433 7.79 53500 2.5922
1.851 7.86 54000 2.5993
1.8313 7.93 54500 2.5960
1.8298 8.0 55000 2.6058
1.8159 8.08 55500 2.6286
1.817 8.15 56000 2.6348
1.8066 8.22 56500 2.6411
1.7935 8.3 57000 2.6338
1.809 8.37 57500 2.6290
1.812 8.44 58000 2.6258
1.79 8.51 58500 2.6321
1.8046 8.59 59000 2.6291
1.7975 8.66 59500 2.6283
1.7968 8.73 60000 2.6284
1.7779 8.81 60500 2.6257
1.7664 8.88 61000 2.6232
1.792 8.95 61500 2.6305
1.7725 9.02 62000 2.6525
1.7563 9.1 62500 2.6794
1.7606 9.17 63000 2.6784
1.7666 9.24 63500 2.6798
1.7551 9.31 64000 2.6813
1.7578 9.39 64500 2.6830
1.7483 9.46 65000 2.6833
1.7431 9.53 65500 2.6884
1.743 9.61 66000 2.6932
1.7395 9.68 66500 2.6927
1.7473 9.75 67000 2.6904
1.7413 9.82 67500 2.6892
1.7437 9.9 68000 2.6898
1.7546 9.97 68500 2.6894
Framework versions
  • Transformers 4.21.0.dev0
  • Pytorch 1.12.0+cu102
  • Datasets 2.3.2
  • Tokenizers 0.12.1

Runs of davanstrien clip-roberta-finetuned on huggingface.co

87
Total runs
2
24-hour runs
-2
3-day runs
-5
7-day runs
-527
30-day runs

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clip-roberta-finetuned huggingface.co is an AI model on huggingface.co that provides clip-roberta-finetuned's model effect (), which can be used instantly with this davanstrien clip-roberta-finetuned model. huggingface.co supports a free trial of the clip-roberta-finetuned model, and also provides paid use of the clip-roberta-finetuned. Support call clip-roberta-finetuned model through api, including Node.js, Python, http.

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https://huggingface.co/davanstrien/clip-roberta-finetuned

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clip-roberta-finetuned huggingface.co is an online trial and call api platform, which integrates clip-roberta-finetuned's modeling effects, including api services, and provides a free online trial of clip-roberta-finetuned, you can try clip-roberta-finetuned online for free by clicking the link below.

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https://huggingface.co/davanstrien/clip-roberta-finetuned

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clip-roberta-finetuned is an open source model from GitHub that offers a free installation service, and any user can find clip-roberta-finetuned on GitHub to install. At the same time, huggingface.co provides the effect of clip-roberta-finetuned install, users can directly use clip-roberta-finetuned installed effect in huggingface.co for debugging and trial. It also supports api for free installation.

clip-roberta-finetuned install url in huggingface.co:

https://huggingface.co/davanstrien/clip-roberta-finetuned

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davanstrien
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