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jgibb
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t-5-base-abs2abs

Text2Text Generation
Transformers
TensorBoard
Safetensors
t5
Generated from Trainer
text-generation-inference
Inference Endpoints
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jgibb commited on
Commit
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1 Parent(s): 412a3e4

training completed[dev]: 512 128

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Files changed (5) hide show
  1. README.md +18 -18
  2. all_results.json +7 -7
  3. runs/Apr01_20-05-07_b59f8bb6c83d/events.out.tfevents.1712001911.b59f8bb6c83d.171.0 +3 -0
  4. test_results.json +7 -7
  5. training_args.bin +1 -1
README.md CHANGED
@@ -19,10 +19,10 @@ should probably proofread and complete it, then remove this comment. -->
19
  This model is a fine-tuned version of [t5-base](https://huggingface.co/t5-base) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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  - Loss: 1.3203
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- - Rouge1: 0.6447
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- - Rouge2: 0.3627
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- - Rougel: 0.5772
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- - Rougelsum: 0.5774
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  - Wer: 0.5292
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  - Bleurt: -0.1862
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@@ -56,20 +56,20 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Wer | Bleurt |
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  |:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:------:|:-------:|
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- | No log | 0.14 | 250 | 1.4708 | 0.6226 | 0.3343 | 0.5515 | 0.5515 | 0.559 | -0.1681 |
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- | 1.9361 | 0.27 | 500 | 1.4181 | 0.6277 | 0.3424 | 0.559 | 0.559 | 0.5498 | -0.1527 |
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- | 1.9361 | 0.41 | 750 | 1.3918 | 0.6327 | 0.3469 | 0.5633 | 0.5634 | 0.5453 | -0.1653 |
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- | 1.5072 | 0.55 | 1000 | 1.3740 | 0.6353 | 0.3509 | 0.5664 | 0.5665 | 0.541 | -0.1653 |
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- | 1.5072 | 0.68 | 1250 | 1.3602 | 0.637 | 0.3529 | 0.5686 | 0.5687 | 0.539 | -0.4817 |
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- | 1.4761 | 0.82 | 1500 | 1.3504 | 0.639 | 0.3557 | 0.5711 | 0.5712 | 0.5361 | -0.1653 |
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- | 1.4761 | 0.96 | 1750 | 1.3424 | 0.64 | 0.3573 | 0.5727 | 0.5728 | 0.5341 | -0.1653 |
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- | 1.4475 | 1.09 | 2000 | 1.3368 | 0.6414 | 0.3587 | 0.5736 | 0.5738 | 0.5329 | -0.4817 |
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- | 1.4475 | 1.23 | 2250 | 1.3324 | 0.6423 | 0.36 | 0.5748 | 0.575 | 0.5316 | -0.4726 |
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- | 1.4375 | 1.36 | 2500 | 1.3280 | 0.6436 | 0.3609 | 0.5757 | 0.5758 | 0.5309 | -0.3069 |
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- | 1.4375 | 1.5 | 2750 | 1.3246 | 0.6442 | 0.3618 | 0.5765 | 0.5766 | 0.5304 | -0.1862 |
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- | 1.4053 | 1.64 | 3000 | 1.3222 | 0.6445 | 0.3622 | 0.5769 | 0.577 | 0.5296 | -0.1862 |
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- | 1.4053 | 1.77 | 3250 | 1.3208 | 0.6448 | 0.3626 | 0.5771 | 0.5772 | 0.5293 | -0.1862 |
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- | 1.3911 | 1.91 | 3500 | 1.3203 | 0.6447 | 0.3627 | 0.5772 | 0.5774 | 0.5292 | -0.1862 |
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  ### Framework versions
 
19
  This model is a fine-tuned version of [t5-base](https://huggingface.co/t5-base) on an unknown dataset.
20
  It achieves the following results on the evaluation set:
21
  - Loss: 1.3203
22
+ - Rouge1: 0.6446
23
+ - Rouge2: 0.3626
24
+ - Rougel: 0.5773
25
+ - Rougelsum: 0.5771
26
  - Wer: 0.5292
27
  - Bleurt: -0.1862
28
 
 
56
 
57
  | Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Wer | Bleurt |
58
  |:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:------:|:-------:|
59
+ | No log | 0.14 | 250 | 1.4708 | 0.6226 | 0.3343 | 0.5514 | 0.5512 | 0.559 | -0.1681 |
60
+ | 1.9361 | 0.27 | 500 | 1.4181 | 0.6277 | 0.3422 | 0.5591 | 0.5588 | 0.5498 | -0.1527 |
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+ | 1.9361 | 0.41 | 750 | 1.3918 | 0.6326 | 0.3467 | 0.5633 | 0.5632 | 0.5453 | -0.1653 |
62
+ | 1.5072 | 0.55 | 1000 | 1.3740 | 0.6352 | 0.3508 | 0.5664 | 0.5662 | 0.541 | -0.1653 |
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+ | 1.5072 | 0.68 | 1250 | 1.3602 | 0.6369 | 0.3528 | 0.5687 | 0.5685 | 0.539 | -0.4817 |
64
+ | 1.4761 | 0.82 | 1500 | 1.3504 | 0.6388 | 0.3557 | 0.5711 | 0.571 | 0.5361 | -0.1653 |
65
+ | 1.4761 | 0.96 | 1750 | 1.3424 | 0.6399 | 0.3573 | 0.5728 | 0.5725 | 0.5341 | -0.1653 |
66
+ | 1.4475 | 1.09 | 2000 | 1.3368 | 0.6413 | 0.3586 | 0.5737 | 0.5735 | 0.5329 | -0.4817 |
67
+ | 1.4475 | 1.23 | 2250 | 1.3324 | 0.6422 | 0.36 | 0.5748 | 0.5746 | 0.5316 | -0.4726 |
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+ | 1.4375 | 1.36 | 2500 | 1.3280 | 0.6435 | 0.3608 | 0.5757 | 0.5754 | 0.5309 | -0.3069 |
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+ | 1.4375 | 1.5 | 2750 | 1.3246 | 0.644 | 0.3618 | 0.5765 | 0.5763 | 0.5304 | -0.1862 |
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+ | 1.4053 | 1.64 | 3000 | 1.3222 | 0.6443 | 0.3622 | 0.5769 | 0.5767 | 0.5296 | -0.1862 |
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+ | 1.4053 | 1.77 | 3250 | 1.3208 | 0.6446 | 0.3625 | 0.5771 | 0.5769 | 0.5293 | -0.1862 |
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+ | 1.3911 | 1.91 | 3500 | 1.3203 | 0.6446 | 0.3626 | 0.5773 | 0.5771 | 0.5292 | -0.1862 |
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  ### Framework versions
all_results.json CHANGED
@@ -2,11 +2,11 @@
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  "test_BLEURT": -0.3441,
3
  "test_WER": 0.5242,
4
  "test_loss": 1.3463356494903564,
5
- "test_rouge1": 0.6465,
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- "test_rouge2": 0.3672,
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- "test_rougeL": 0.5816,
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- "test_rougeLsum": 0.5818,
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- "test_runtime": 31.1185,
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- "test_samples_per_second": 11.794,
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- "test_steps_per_second": 1.992
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  }
 
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  "test_BLEURT": -0.3441,
3
  "test_WER": 0.5242,
4
  "test_loss": 1.3463356494903564,
5
+ "test_rouge1": 0.6462,
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+ "test_rouge2": 0.3679,
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+ "test_rougeL": 0.5818,
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+ "test_rougeLsum": 0.5816,
9
+ "test_runtime": 33.8733,
10
+ "test_samples_per_second": 10.834,
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+ "test_steps_per_second": 1.83
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  }
runs/Apr01_20-05-07_b59f8bb6c83d/events.out.tfevents.1712001911.b59f8bb6c83d.171.0 ADDED
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test_results.json CHANGED
@@ -2,11 +2,11 @@
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  "test_BLEURT": -0.3441,
3
  "test_WER": 0.5242,
4
  "test_loss": 1.3463356494903564,
5
- "test_rouge1": 0.6465,
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- "test_rouge2": 0.3672,
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- "test_rougeL": 0.5816,
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- "test_rougeLsum": 0.5818,
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- "test_runtime": 31.1185,
10
- "test_samples_per_second": 11.794,
11
- "test_steps_per_second": 1.992
12
  }
 
2
  "test_BLEURT": -0.3441,
3
  "test_WER": 0.5242,
4
  "test_loss": 1.3463356494903564,
5
+ "test_rouge1": 0.6462,
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+ "test_rouge2": 0.3679,
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+ "test_rougeL": 0.5818,
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+ "test_rougeLsum": 0.5816,
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+ "test_runtime": 33.8733,
10
+ "test_samples_per_second": 10.834,
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+ "test_steps_per_second": 1.83
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  }
training_args.bin CHANGED
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