training completed[dev]: 512 128

README.md

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+---
+license: apache-2.0
+base_model: t5-base
+tags:
+- generated_from_trainer
+metrics:
+- rouge
+- wer
+model-index:
+- name: t-5-base-abs2abs
+  results: []
+---
+
+<!-- This model card has been generated automatically according to the information the Trainer had access to. You
+should probably proofread and complete it, then remove this comment. -->
+
+# t-5-base-abs2abs
+
+This model is a fine-tuned version of [t5-base](https://huggingface.co/t5-base) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 1.3203
+- Rouge1: 0.6447
+- Rouge2: 0.3627
+- Rougel: 0.5772
+- Rougelsum: 0.5774
+- Wer: 0.5292
+- Bleurt: -0.1862
+
+## 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: 2e-05
+- train_batch_size: 6
+- eval_batch_size: 6
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 2
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Wer    | Bleurt  |
+|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:------:|:-------:|
+| No log        | 0.14  | 250  | 1.4708          | 0.6226 | 0.3343 | 0.5515 | 0.5515    | 0.559  | -0.1681 |
+| 1.9361        | 0.27  | 500  | 1.4181          | 0.6277 | 0.3424 | 0.559  | 0.559     | 0.5498 | -0.1527 |
+| 1.9361        | 0.41  | 750  | 1.3918          | 0.6327 | 0.3469 | 0.5633 | 0.5634    | 0.5453 | -0.1653 |
+| 1.5072        | 0.55  | 1000 | 1.3740          | 0.6353 | 0.3509 | 0.5664 | 0.5665    | 0.541  | -0.1653 |
+| 1.5072        | 0.68  | 1250 | 1.3602          | 0.637  | 0.3529 | 0.5686 | 0.5687    | 0.539  | -0.4817 |
+| 1.4761        | 0.82  | 1500 | 1.3504          | 0.639  | 0.3557 | 0.5711 | 0.5712    | 0.5361 | -0.1653 |
+| 1.4761        | 0.96  | 1750 | 1.3424          | 0.64   | 0.3573 | 0.5727 | 0.5728    | 0.5341 | -0.1653 |
+| 1.4475        | 1.09  | 2000 | 1.3368          | 0.6414 | 0.3587 | 0.5736 | 0.5738    | 0.5329 | -0.4817 |
+| 1.4475        | 1.23  | 2250 | 1.3324          | 0.6423 | 0.36   | 0.5748 | 0.575     | 0.5316 | -0.4726 |
+| 1.4375        | 1.36  | 2500 | 1.3280          | 0.6436 | 0.3609 | 0.5757 | 0.5758    | 0.5309 | -0.3069 |
+| 1.4375        | 1.5   | 2750 | 1.3246          | 0.6442 | 0.3618 | 0.5765 | 0.5766    | 0.5304 | -0.1862 |
+| 1.4053        | 1.64  | 3000 | 1.3222          | 0.6445 | 0.3622 | 0.5769 | 0.577     | 0.5296 | -0.1862 |
+| 1.4053        | 1.77  | 3250 | 1.3208          | 0.6448 | 0.3626 | 0.5771 | 0.5772    | 0.5293 | -0.1862 |
+| 1.3911        | 1.91  | 3500 | 1.3203          | 0.6447 | 0.3627 | 0.5772 | 0.5774    | 0.5292 | -0.1862 |
+
+
+### Framework versions
+
+- Transformers 4.38.2
+- Pytorch 2.2.1+cu121
+- Datasets 2.18.0
+- Tokenizers 0.15.2

all_results.json

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+{
+    "test_BLEURT": -0.3441,
+    "test_WER": 0.5242,
+    "test_loss": 1.3463356494903564,
+    "test_rouge1": 0.6465,
+    "test_rouge2": 0.3672,
+    "test_rougeL": 0.5816,
+    "test_rougeLsum": 0.5818,
+    "test_runtime": 31.1185,
+    "test_samples_per_second": 11.794,
+    "test_steps_per_second": 1.992
+}

generation_config.json

@@ -0,0 +1,7 @@
+{
+  "_from_model_config": true,
+  "decoder_start_token_id": 0,
+  "eos_token_id": 1,
+  "pad_token_id": 0,
+  "transformers_version": "4.38.2"
+}

runs/Mar30_22-53-53_93badbe1494c/events.out.tfevents.1711839244.93badbe1494c.1089.3

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+oid sha256:e9338ed993fee1185e3881f66139a088a45ec79e452dae688ee87ba238bbbb8b
+size 15393

test_results.json

@@ -0,0 +1,12 @@
+{
+    "test_BLEURT": -0.3441,
+    "test_WER": 0.5242,
+    "test_loss": 1.3463356494903564,
+    "test_rouge1": 0.6465,
+    "test_rouge2": 0.3672,
+    "test_rougeL": 0.5816,
+    "test_rougeLsum": 0.5818,
+    "test_runtime": 31.1185,
+    "test_samples_per_second": 11.794,
+    "test_steps_per_second": 1.992
+}