Training in progress, step 500

.gitattributes

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README.md

@@ -0,0 +1,75 @@
+---
+license: apache-2.0
+base_model: google/mt5-base
+tags:
+- generated_from_trainer
+metrics:
+- rouge
+model-index:
+- name: mt5-base-finetuned-test_63829_prefix_summarize
+  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. -->
+
+# mt5-base-finetuned-test_63829_prefix_summarize
+
+This model is a fine-tuned version of [google/mt5-base](https://huggingface.co/google/mt5-base) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 2.3498
+- Rouge1: 11.28
+- Rouge2: 3.5248
+- Rougel: 9.174
+- Rougelsum: 10.6313
+- Gen Len: 19.0
+
+## 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: 2
+- eval_batch_size: 2
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 15
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Rouge1  | Rouge2 | Rougel | Rougelsum | Gen Len |
+|:-------------:|:-----:|:----:|:---------------:|:-------:|:------:|:------:|:---------:|:-------:|
+| 7.6624        | 1.25  | 500  | 2.6231          | 7.333   | 2.0471 | 6.2456 | 7.0157    | 14.01   |
+| 3.3306        | 2.5   | 1000 | 2.5079          | 10.5135 | 3.0104 | 8.4645 | 9.8798    | 19.0    |
+| 3.1123        | 3.75  | 1500 | 2.4512          | 10.5261 | 3.3739 | 8.6176 | 9.8711    | 19.0    |
+| 2.9927        | 5.0   | 2000 | 2.4137          | 11.14   | 3.5973 | 9.2204 | 10.407    | 19.0    |
+| 2.8765        | 6.25  | 2500 | 2.4050          | 10.9669 | 3.7633 | 9.1517 | 10.283    | 19.0    |
+| 2.8211        | 7.5   | 3000 | 2.3828          | 11.6779 | 4.181  | 9.8295 | 10.9657   | 19.0    |
+| 2.7589        | 8.75  | 3500 | 2.3756          | 11.6097 | 4.1335 | 9.7619 | 10.8368   | 19.0    |
+| 2.722         | 10.0  | 4000 | 2.3627          | 11.8385 | 4.0634 | 9.6721 | 10.9386   | 19.0    |
+| 2.6781        | 11.25 | 4500 | 2.3611          | 11.3415 | 3.5812 | 9.1328 | 10.6537   | 19.0    |
+| 2.6648        | 12.5  | 5000 | 2.3524          | 11.3808 | 3.6088 | 9.2331 | 10.6316   | 19.0    |
+| 2.6404        | 13.75 | 5500 | 2.3521          | 11.3031 | 3.5165 | 9.1629 | 10.6573   | 19.0    |
+| 2.6397        | 15.0  | 6000 | 2.3498          | 11.28   | 3.5248 | 9.174  | 10.6313   | 19.0    |
+
+
+### Framework versions
+
+- Transformers 4.32.1
+- Pytorch 2.1.0
+- Datasets 2.12.0
+- Tokenizers 0.13.3

config.json

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+{
+  "_name_or_path": "google/mt5-base",
+  "architectures": [
+    "MT5ForConditionalGeneration"
+  ],
+  "classifier_dropout": 0.0,
+  "d_ff": 2048,
+  "d_kv": 64,
+  "d_model": 768,
+  "decoder_start_token_id": 0,
+  "dense_act_fn": "gelu_new",
+  "dropout_rate": 0.1,
+  "eos_token_id": 1,
+  "feed_forward_proj": "gated-gelu",
+  "initializer_factor": 1.0,
+  "is_encoder_decoder": true,
+  "is_gated_act": true,
+  "layer_norm_epsilon": 1e-06,
+  "length_penalty": 0.6,
+  "max_length": 500,
+  "model_type": "mt5",
+  "no_repeat_ngram_size": 2,
+  "num_beams": 15,
+  "num_decoder_layers": 12,
+  "num_heads": 12,
+  "num_layers": 12,
+  "output_past": true,
+  "pad_token_id": 0,
+  "relative_attention_max_distance": 128,
+  "relative_attention_num_buckets": 32,
+  "tie_word_embeddings": false,
+  "tokenizer_class": "T5Tokenizer",
+  "torch_dtype": "float32",
+  "transformers_version": "4.32.1",
+  "use_cache": true,
+  "vocab_size": 250112
+}

generation_config.json

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+  "eos_token_id": 1,
+  "pad_token_id": 0,
+  "transformers_version": "4.32.1"
+}

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tokenizer_config.json

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