t5_recommendation_sports_equipment

README.md

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+---
+license: apache-2.0
+base_model: t5-large
+tags:
+- generated_from_trainer
+metrics:
+- rouge
+model-index:
+- name: t5_recommendation_sports_equipment_english
+  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. -->
+
+# t5_recommendation_sports_equipment_english
+
+This model is a fine-tuned version of [t5-large](https://huggingface.co/t5-large) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.4020
+- Rouge1: 57.9365
+- Rouge2: 47.6190
+- Rougel: 57.9365
+- Rougelsum: 57.9365
+- Gen Len: 4.1429
+
+## 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: 0.0001
+- train_batch_size: 4
+- eval_batch_size: 4
+- seed: 42
+- gradient_accumulation_steps: 4
+- total_train_batch_size: 16
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 10
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum | Gen Len |
+|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
+| No log        | 0.96  | 6    | 7.7857          | 20.2721 | 10.3896 | 20.0454 | 20.9524   | 11.3810 |
+| No log        | 1.92  | 12   | 3.1922          | 20.0    | 4.7619  | 20.4762 | 20.4762   | 3.1905  |
+| No log        | 2.88  | 18   | 0.8028          | 5.5556  | 0.0     | 5.5556  | 5.5556    | 3.0     |
+| No log        | 4.0   | 25   | 0.7207          | 32.8571 | 19.0476 | 32.9365 | 34.0476   | 3.2381  |
+| No log        | 4.96  | 31   | 0.5217          | 50.3968 | 42.8571 | 50.0    | 50.7937   | 3.9524  |
+| No log        | 5.92  | 37   | 0.4420          | 57.9365 | 47.6190 | 57.9365 | 57.9365   | 4.0476  |
+| No log        | 6.88  | 43   | 0.4694          | 67.4603 | 61.9048 | 67.4603 | 67.4603   | 4.0     |
+| No log        | 8.0   | 50   | 0.4408          | 57.9365 | 47.6190 | 57.9365 | 57.9365   | 4.1429  |
+| No log        | 8.96  | 56   | 0.4269          | 57.9365 | 47.6190 | 57.9365 | 57.9365   | 4.1429  |
+| No log        | 9.6   | 60   | 0.4020          | 57.9365 | 47.6190 | 57.9365 | 57.9365   | 4.1429  |
+
+
+### Framework versions
+
+- Transformers 4.33.2
+- Pytorch 2.0.1+cu118
+- Datasets 2.8.0
+- Tokenizers 0.13.3

config.json

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+{
+  "_name_or_path": "t5-large",
+  "architectures": [
+    "T5ForConditionalGeneration"
+  ],
+  "classifier_dropout": 0.0,
+  "d_ff": 4096,
+  "d_kv": 64,
+  "d_model": 1024,
+  "decoder_start_token_id": 0,
+  "dense_act_fn": "relu",
+  "dropout_rate": 0.1,
+  "eos_token_id": 1,
+  "feed_forward_proj": "relu",
+  "initializer_factor": 1.0,
+  "is_encoder_decoder": true,
+  "is_gated_act": false,
+  "layer_norm_epsilon": 1e-06,
+  "model_type": "t5",
+  "n_positions": 512,
+  "num_decoder_layers": 24,
+  "num_heads": 16,
+  "num_layers": 24,
+  "output_past": true,
+  "pad_token_id": 0,
+  "relative_attention_max_distance": 128,
+  "relative_attention_num_buckets": 32,
+  "task_specific_params": {
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+      "min_length": 30,
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+    },
+    "translation_en_to_de": {
+      "early_stopping": true,
+      "max_length": 300,
+      "num_beams": 4,
+      "prefix": "translate English to German: "
+    },
+    "translation_en_to_fr": {
+      "early_stopping": true,
+      "max_length": 300,
+      "num_beams": 4,
+      "prefix": "translate English to French: "
+    },
+    "translation_en_to_ro": {
+      "early_stopping": true,
+      "max_length": 300,
+      "num_beams": 4,
+      "prefix": "translate English to Romanian: "
+    }
+  },
+  "torch_dtype": "float32",
+  "transformers_version": "4.33.2",
+  "use_cache": true,
+  "vocab_size": 32128
+}

generation_config.json

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+}

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