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grandpythia-200k-70m

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metadata
license: apache-2.0
base_model: EleutherAI/pythia-70m-deduped
tags:
  - generated_from_trainer
model-index:
  - name: grandpythia-200k-70m
    results: []

grandpythia-200k-70m

This model is a fine-tuned version of EleutherAI/pythia-70m-deduped on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 0.8419

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: 64
  • eval_batch_size: 64
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: cosine
  • num_epochs: 1

Training results

Training Loss Epoch Step Validation Loss
1.1766 0.01 68 1.2007
1.0903 0.02 136 1.1284
1.0809 0.03 204 1.0993
1.0928 0.04 272 1.0712
0.989 0.05 340 1.0473
1.0044 0.06 408 1.0373
0.985 0.07 476 1.0241
1.0272 0.08 544 1.0130
1.0295 0.09 612 1.0036
1.0172 0.1 680 0.9985
0.9582 0.11 748 0.9924
1.0342 0.12 816 0.9916
1.0053 0.13 884 0.9844
0.9321 0.14 952 0.9798
0.9473 0.15 1020 0.9727
0.9197 0.16 1088 0.9688
0.9827 0.17 1156 0.9632
0.9423 0.18 1224 0.9613
0.9662 0.19 1292 0.9578
0.9417 0.2 1360 0.9549
0.9501 0.21 1428 0.9461
0.9744 0.22 1496 0.9466
0.8693 0.23 1564 0.9394
0.9467 0.24 1632 0.9393
0.9274 0.25 1700 0.9362
0.8793 0.26 1768 0.9338
0.99 0.27 1836 0.9276
0.8983 0.28 1904 0.9291
0.9177 0.29 1972 0.9246
0.9586 0.3 2040 0.9224
0.9364 0.31 2108 0.9178
0.9248 0.32 2176 0.9175
0.9294 0.33 2244 0.9171
0.9142 0.34 2312 0.9136
0.9533 0.35 2380 0.9102
0.9193 0.36 2448 0.9094
0.9072 0.37 2516 0.9075
0.8927 0.38 2584 0.9043
0.9055 0.39 2652 0.9032
0.9276 0.4 2720 0.9030
0.8847 0.41 2788 0.8966
0.9449 0.42 2856 0.8963
0.8754 0.43 2924 0.8971
0.8612 0.44 2992 0.8935
0.9028 0.45 3060 0.8895
0.8641 0.46 3128 0.8925
0.8668 0.47 3196 0.8887
0.8935 0.48 3264 0.8863
0.8889 0.49 3332 0.8837
0.8854 0.5 3400 0.8849
0.8725 0.51 3468 0.8831
0.9425 0.52 3536 0.8796
0.8577 0.53 3604 0.8780
0.8281 0.54 3672 0.8747
0.9141 0.55 3740 0.8736
0.8684 0.56 3808 0.8738
0.8476 0.57 3876 0.8718
0.8761 0.58 3944 0.8735
0.8464 0.59 4012 0.8708
0.8732 0.6 4080 0.8681
0.9441 0.61 4148 0.8669
0.881 0.62 4216 0.8657
0.8635 0.63 4284 0.8640
0.827 0.64 4352 0.8625
0.9123 0.65 4420 0.8628
0.8557 0.66 4488 0.8605
0.8157 0.67 4556 0.8591
0.9008 0.68 4624 0.8580
0.8574 0.69 4692 0.8580
0.8374 0.7 4760 0.8563
0.8698 0.71 4828 0.8554
0.8817 0.72 4896 0.8545
0.8375 0.73 4964 0.8532
0.8504 0.74 5032 0.8524
0.8526 0.75 5100 0.8516
0.9306 0.76 5168 0.8511
0.7999 0.77 5236 0.8502
0.8337 0.78 5304 0.8495
0.7934 0.79 5372 0.8488
0.8159 0.8 5440 0.8480
0.7997 0.81 5508 0.8473
0.8909 0.82 5576 0.8470
0.852 0.83 5644 0.8461
0.8285 0.84 5712 0.8455
0.8437 0.85 5780 0.8448
0.8784 0.86 5848 0.8444
0.8123 0.87 5916 0.8440
0.8439 0.88 5984 0.8436
0.8847 0.89 6052 0.8433
0.8165 0.9 6120 0.8429
0.8405 0.91 6188 0.8427
0.8641 0.92 6256 0.8425
0.8536 0.93 6324 0.8424
0.8426 0.94 6392 0.8421
0.8547 0.95 6460 0.8421
0.8144 0.96 6528 0.8419
0.8475 0.97 6596 0.8419
0.8063 0.98 6664 0.8419
0.7943 0.99 6732 0.8419

Framework versions

  • Transformers 4.38.2
  • Pytorch 2.1.0+cu121
  • Datasets 2.18.0
  • Tokenizers 0.15.2