Training in progress, step 500

.gitattributes

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 *.zip filter=lfs diff=lfs merge=lfs -text
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+tokenizer.json filter=lfs diff=lfs merge=lfs -text

README.md

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+---
+license: apache-2.0
+base_model: emilstabil/mt5-base_V25775_V44105
+tags:
+- generated_from_trainer
+metrics:
+- rouge
+model-index:
+- name: mt5-base_V25775_V44105_V65464
+  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_V25775_V44105_V65464
+
+This model is a fine-tuned version of [emilstabil/mt5-base_V25775_V44105](https://huggingface.co/emilstabil/mt5-base_V25775_V44105) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 2.2155
+- Rouge1: 31.936
+- Rouge2: 11.6826
+- Rougel: 21.8491
+- Rougelsum: 26.1962
+- Gen Len: 86.4335
+
+## 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: 3
+- eval_batch_size: 3
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 20
+
+### Training results
+
+| Training Loss | Epoch | Step  | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum | Gen Len |
+|:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
+| 1.794         | 0.81  | 500   | 2.1891          | 29.9862 | 11.266  | 20.9904 | 24.6444   | 83.9571 |
+| 1.7476        | 1.61  | 1000  | 2.1461          | 29.9736 | 10.782  | 20.6739 | 24.663    | 80.7039 |
+| 1.7381        | 2.42  | 1500  | 2.1835          | 30.4805 | 11.0774 | 21.0063 | 24.9859   | 85.1545 |
+| 1.6956        | 3.23  | 2000  | 2.1836          | 30.0028 | 10.9574 | 20.721  | 24.5095   | 79.6266 |
+| 1.6593        | 4.03  | 2500  | 2.1878          | 29.7076 | 10.7504 | 20.4333 | 24.3183   | 77.3948 |
+| 1.6416        | 4.84  | 3000  | 2.1937          | 30.4163 | 11.0254 | 20.9501 | 24.8448   | 82.9185 |
+| 1.613         | 5.65  | 3500  | 2.2060          | 30.518  | 11.1385 | 21.0192 | 24.9011   | 80.5408 |
+| 1.6199        | 6.45  | 4000  | 2.2267          | 30.7458 | 11.2048 | 21.3743 | 25.2027   | 82.6524 |
+| 1.5769        | 7.26  | 4500  | 2.2113          | 31.6325 | 11.4758 | 21.3606 | 25.8015   | 88.4292 |
+| 1.5765        | 8.06  | 5000  | 2.2101          | 31.3878 | 11.2897 | 21.3136 | 25.729    | 86.4936 |
+| 1.5706        | 8.87  | 5500  | 2.2115          | 32.2878 | 11.5704 | 21.9421 | 26.3874   | 91.7768 |
+| 1.5625        | 9.68  | 6000  | 2.2145          | 31.5711 | 11.4538 | 21.3608 | 25.8527   | 88.7167 |
+| 1.5278        | 10.48 | 6500  | 2.2219          | 30.6581 | 11.2777 | 21.1534 | 25.0079   | 80.9785 |
+| 1.5295        | 11.29 | 7000  | 2.2340          | 30.6276 | 11.0522 | 21.1302 | 25.0254   | 82.7854 |
+| 1.5286        | 12.1  | 7500  | 2.2155          | 30.614  | 11.4733 | 21.3702 | 25.0853   | 78.309  |
+| 1.5138        | 12.9  | 8000  | 2.2298          | 30.6334 | 11.3644 | 21.1625 | 25.0588   | 81.133  |
+| 1.4935        | 13.71 | 8500  | 2.2163          | 31.0745 | 11.1841 | 21.1997 | 25.3718   | 84.8412 |
+| 1.5309        | 14.52 | 9000  | 2.2133          | 31.0237 | 11.5053 | 21.5787 | 25.6145   | 80.7725 |
+| 1.4852        | 15.32 | 9500  | 2.2239          | 31.9443 | 11.5394 | 21.5817 | 26.0822   | 88.2532 |
+| 1.5247        | 16.13 | 10000 | 2.2258          | 31.6514 | 11.6206 | 21.5841 | 25.8946   | 85.6052 |
+| 1.4931        | 16.94 | 10500 | 2.2205          | 31.522  | 11.5251 | 21.1916 | 25.587    | 87.8069 |
+| 1.5085        | 17.74 | 11000 | 2.2110          | 31.4641 | 11.3441 | 21.3223 | 25.7801   | 85.7983 |
+| 1.5014        | 18.55 | 11500 | 2.2162          | 31.5727 | 11.6335 | 21.6467 | 25.949    | 84.2918 |
+| 1.5057        | 19.35 | 12000 | 2.2155          | 31.936  | 11.6826 | 21.8491 | 26.1962   | 86.4335 |
+
+
+### 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": "emilstabil/mt5-base_V25775_V44105",
+  "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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+  "decoder_start_token_id": 0,
+  "eos_token_id": 1,
+  "length_penalty": 0.6,
+  "max_length": 500,
+  "no_repeat_ngram_size": 2,
+  "num_beams": 15,
+  "pad_token_id": 0,
+  "transformers_version": "4.32.1"
+}

pytorch_model.bin

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special_tokens_map.json

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tokenizer_config.json

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+  "tokenizer_class": "T5Tokenizer",
+  "truncation_side": "right",
+  "truncation_strategy": "longest_first",
+  "unk_token": "<unk>"
+}

training_args.bin

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