Add new SentenceTransformer model

README.md

@@ -83,28 +83,28 @@ model-index:
       type: test
     metrics:
     - type: cosine_accuracy@1
-      value: 0.5955802603036876
+      value: 0.5953768980477223
       name: Cosine Accuracy@1
     - type: cosine_precision@1
-      value: 0.5955802603036876
+      value: 0.5953768980477223
       name: Cosine Precision@1
     - type: cosine_recall@1
-      value: 0.5780913232288468
+      value: 0.5778879609728815
       name: Cosine Recall@1
     - type: cosine_ndcg@10
-      value: 0.777639866271746
+      value: 0.7775436499957671
       name: Cosine Ndcg@10
     - type: cosine_mrr@1
-      value: 0.5955802603036876
+      value: 0.5953768980477223
       name: Cosine Mrr@1
     - type: cosine_map@100
-      value: 0.7275779687157514
+      value: 0.7274666565910912
       name: Cosine Map@100
     - type: cosine_auc_precision_cache_hit_ratio
-      value: 0.3639683124583609
+      value: 0.36387321267916206
       name: Cosine Auc Precision Cache Hit Ratio
     - type: cosine_auc_similarity_distribution
-      value: 0.15401896350374616
+      value: 0.15403918371209657
       name: Cosine Auc Similarity Distribution
 ---
 
@@ -169,9 +169,9 @@ print(embeddings.shape)
 # Get the similarity scores for the embeddings
 similarities = model.similarity(embeddings, embeddings)
 print(similarities)
-# tensor([[1.0000, 1.0000, 0.8359],
-#         [1.0000, 1.0000, 0.8359],
-#         [0.8359, 0.8359, 0.9961]], dtype=torch.bfloat16)
+# tensor([[1.0000, 1.0000, 0.8251],
+#         [1.0000, 1.0000, 0.8251],
+#         [0.8251, 0.8251, 1.0000]])
 ```
 
 <!--
@@ -209,13 +209,13 @@ You can finetune this model on your own dataset.
 
 | Metric                               | Value      |
 |:-------------------------------------|:-----------|
-| cosine_accuracy@1                    | 0.5956     |
-| cosine_precision@1                   | 0.5956     |
-| cosine_recall@1                      | 0.5781     |
-| **cosine_ndcg@10**                   | **0.7776** |
-| cosine_mrr@1                         | 0.5956     |
-| cosine_map@100                       | 0.7276     |
-| cosine_auc_precision_cache_hit_ratio | 0.364      |
+| cosine_accuracy@1                    | 0.5954     |
+| cosine_precision@1                   | 0.5954     |
+| cosine_recall@1                      | 0.5779     |
+| **cosine_ndcg@10**                   | **0.7775** |
+| cosine_mrr@1                         | 0.5954     |
+| cosine_map@100                       | 0.7275     |
+| cosine_auc_precision_cache_hit_ratio | 0.3639     |
 | cosine_auc_similarity_distribution   | 0.154      |
 
 <!--
@@ -286,10 +286,157 @@ You can finetune this model on your own dataset.
   }
   ```
 
+### Training Hyperparameters
+#### Non-Default Hyperparameters
+
+- `eval_strategy`: steps
+- `per_device_train_batch_size`: 300
+- `per_device_eval_batch_size`: 300
+- `gradient_accumulation_steps`: 2
+- `weight_decay`: 0.001
+- `adam_beta2`: 0.98
+- `adam_epsilon`: 1e-06
+- `num_train_epochs`: 1
+- `warmup_ratio`: 0.05
+- `bf16`: True
+- `dataloader_num_workers`: 4
+- `dataloader_prefetch_factor`: 4
+- `load_best_model_at_end`: True
+- `optim`: stable_adamw
+- `ddp_find_unused_parameters`: False
+- `dataloader_persistent_workers`: True
+- `push_to_hub`: True
+- `hub_model_id`: redis/langcache-embed-v3
+- `batch_sampler`: no_duplicates
+
+#### All Hyperparameters
+<details><summary>Click to expand</summary>
+
+- `overwrite_output_dir`: False
+- `do_predict`: False
+- `eval_strategy`: steps
+- `prediction_loss_only`: True
+- `per_device_train_batch_size`: 300
+- `per_device_eval_batch_size`: 300
+- `per_gpu_train_batch_size`: None
+- `per_gpu_eval_batch_size`: None
+- `gradient_accumulation_steps`: 2
+- `eval_accumulation_steps`: None
+- `torch_empty_cache_steps`: None
+- `learning_rate`: 5e-05
+- `weight_decay`: 0.001
+- `adam_beta1`: 0.9
+- `adam_beta2`: 0.98
+- `adam_epsilon`: 1e-06
+- `max_grad_norm`: 1.0
+- `num_train_epochs`: 1
+- `max_steps`: -1
+- `lr_scheduler_type`: linear
+- `lr_scheduler_kwargs`: {}
+- `warmup_ratio`: 0.05
+- `warmup_steps`: 0
+- `log_level`: passive
+- `log_level_replica`: warning
+- `log_on_each_node`: True
+- `logging_nan_inf_filter`: True
+- `save_safetensors`: True
+- `save_on_each_node`: False
+- `save_only_model`: False
+- `restore_callback_states_from_checkpoint`: False
+- `no_cuda`: False
+- `use_cpu`: False
+- `use_mps_device`: False
+- `seed`: 42
+- `data_seed`: None
+- `jit_mode_eval`: False
+- `use_ipex`: False
+- `bf16`: True
+- `fp16`: False
+- `fp16_opt_level`: O1
+- `half_precision_backend`: auto
+- `bf16_full_eval`: False
+- `fp16_full_eval`: False
+- `tf32`: None
+- `local_rank`: 0
+- `ddp_backend`: None
+- `tpu_num_cores`: None
+- `tpu_metrics_debug`: False
+- `debug`: []
+- `dataloader_drop_last`: False
+- `dataloader_num_workers`: 4
+- `dataloader_prefetch_factor`: 4
+- `past_index`: -1
+- `disable_tqdm`: False
+- `remove_unused_columns`: True
+- `label_names`: None
+- `load_best_model_at_end`: True
+- `ignore_data_skip`: False
+- `fsdp`: []
+- `fsdp_min_num_params`: 0
+- `fsdp_config`: {'min_num_params': 0, 'xla': False, 'xla_fsdp_v2': False, 'xla_fsdp_grad_ckpt': False}
+- `fsdp_transformer_layer_cls_to_wrap`: None
+- `accelerator_config`: {'split_batches': False, 'dispatch_batches': None, 'even_batches': True, 'use_seedable_sampler': True, 'non_blocking': False, 'gradient_accumulation_kwargs': None}
+- `parallelism_config`: None
+- `deepspeed`: None
+- `label_smoothing_factor`: 0.0
+- `optim`: stable_adamw
+- `optim_args`: None
+- `adafactor`: False
+- `group_by_length`: False
+- `length_column_name`: length
+- `ddp_find_unused_parameters`: False
+- `ddp_bucket_cap_mb`: None
+- `ddp_broadcast_buffers`: False
+- `dataloader_pin_memory`: True
+- `dataloader_persistent_workers`: True
+- `skip_memory_metrics`: True
+- `use_legacy_prediction_loop`: False
+- `push_to_hub`: True
+- `resume_from_checkpoint`: None
+- `hub_model_id`: redis/langcache-embed-v3
+- `hub_strategy`: every_save
+- `hub_private_repo`: None
+- `hub_always_push`: False
+- `hub_revision`: None
+- `gradient_checkpointing`: False
+- `gradient_checkpointing_kwargs`: None
+- `include_inputs_for_metrics`: False
+- `include_for_metrics`: []
+- `eval_do_concat_batches`: True
+- `fp16_backend`: auto
+- `push_to_hub_model_id`: None
+- `push_to_hub_organization`: None
+- `mp_parameters`: 
+- `auto_find_batch_size`: False
+- `full_determinism`: False
+- `torchdynamo`: None
+- `ray_scope`: last
+- `ddp_timeout`: 1800
+- `torch_compile`: False
+- `torch_compile_backend`: None
+- `torch_compile_mode`: None
+- `include_tokens_per_second`: False
+- `include_num_input_tokens_seen`: False
+- `neftune_noise_alpha`: None
+- `optim_target_modules`: None
+- `batch_eval_metrics`: False
+- `eval_on_start`: False
+- `use_liger_kernel`: False
+- `liger_kernel_config`: None
+- `eval_use_gather_object`: False
+- `average_tokens_across_devices`: False
+- `prompts`: None
+- `batch_sampler`: no_duplicates
+- `multi_dataset_batch_sampler`: proportional
+- `router_mapping`: {}
+- `learning_rate_mapping`: {}
+
+</details>
+
 ### Training Logs
 | Epoch | Step | test_cosine_ndcg@10 |
 |:-----:|:----:|:-------------------:|
-| -1    | -1   | 0.7776              |
+| -1    | -1   | 0.7775              |
 
 
 ### Framework Versions