---
tags:
- sentence-transformers
- sentence-similarity
- feature-extraction
- dense
- generated_from_trainer
- dataset_size:4615
- loss:TripletLoss
base_model: sentence-transformers/all-mpnet-base-v2
widget:
- source_sentence: Do you ever feel like you have failed in life or let yourself down?
sentences:
- But I just don't feel like even getting started because I know that I will fail
again.
- I cant remember the last time I felt happiness.
- That was their biggest and last mistake.
- source_sentence: Do you feel sad or unhappy?
sentences:
- I have been depressed since late September so I feel you.
- I share a lot of your traits, and considered myself a failure too.
- He conveys that feeling of regret so well I can feel it everytime
- source_sentence: Do you feel hopeful about your future or do things seem hopeless?
sentences:
- I'm pretty optimistic though since the pace of technological growth is accelerating
so rapidly.
- '[For a clickable image, click here](http://futurism.com/thisweekinscience)
[To get these images directly to your inbox, sign up here](http://futurism.com/subscribe)
_
Sources | Reddit
--- | ---
[Oldest and Furthest Galaxy](http://futurism.com/links/astronomers-discover-the-oldest-and-farthest-known-galaxy/)
| [Reddit](https://www.reddit.com/r/science/comments/3jypyf/researchers_find_132_billion_yearold_galaxy_in/)
[3D Printed Ribs ](http://futurism.com/links/these-3d-printed-titanium-ribs-were-successfully-implanted-in-a-person/)
| [Reddit](https://www.reddit.com/r/technology/comments/3kj8pf/patient_receives_3dprinted_titanium_sternum_and/?ref=search_posts)
[Chinese Far Side of Moon] (http://m.phys.org/news/2015-09-china-aims-probe-moon-side.html) |
[Reddit](https://www.reddit.com/r/worldnews/comments/3kcsg5/china_to_explore_dark_side_of_the_moon_china_has/)
[Rugby Ball Molecule](http://www.forbes.com/sites/carmendrahl/2015/09/02/giant-rugby-ball-new-interaction-chemistry/)
| [Reddit](https://www.reddit.com/r/EverythingScience/comments/3krt22/this_giant_rugby_ball_contains_a_new_chemical/)
[Measuring the Universe](http://astronomynow.com/2015/09/04/using-stellar-twins-to-climb-the-cosmic-distance-ladder/)
| [Reddit](https://www.reddit.com/r/science/comments/3jum8c/astronomers_have_developed_a_new_highly_accurate/)
[3D Printed Stethoscope ](http://futurism.com/links/3d-printed-stethoscopes-cost-as-little-as-2-50-and-are-just-as-good/)
| [Reddit](https://www.reddit.com/r/news/comments/3kgboz/doctor_3d_prints_stethoscope_to_alleviate_supply/)
[Giant Structure in Universe](http://phys.org/news/2015-09-giant-ring-like-universe.html)
| [Reddit](https://www.reddit.com/r/EverythingScience/comments/3jzjlm/surprising_giant_ringlike_structure_in_the/)
[Recoded Cell Factories](http://m.phys.org/news/2015-09-recoded-cells-factories-proteins.html)
| [Reddit](https://www.reddit.com/r/EverythingScience/comments/3krux3/researchers_transform_recoded_cells_into/)'
- I do not expect things to work out for me.
- source_sentence: Do you feel sad or unhappy?
sentences:
- Me everyday im depressing
- And now I feel very alone and useless.
- Sucks that I'm not the only one because others are suffering, but it's nice to
know I'm not alone.
- source_sentence: Do you feel sad or unhappy?
sentences:
- I cried because I lost not only my money, but because I lost myself.
- Im not exactly depressed, at least not all of the time.
- does anyone feel like they cant be sad
pipeline_tag: sentence-similarity
library_name: sentence-transformers
---
# SentenceTransformer based on sentence-transformers/all-mpnet-base-v2
This is a [sentence-transformers](https://www.SBERT.net) model finetuned from [sentence-transformers/all-mpnet-base-v2](https://huggingface.co/sentence-transformers/all-mpnet-base-v2). It maps sentences & paragraphs to a 768-dimensional dense vector space and can be used for semantic textual similarity, semantic search, paraphrase mining, text classification, clustering, and more.
## Model Details
### Model Description
- **Model Type:** Sentence Transformer
- **Base model:** [sentence-transformers/all-mpnet-base-v2](https://huggingface.co/sentence-transformers/all-mpnet-base-v2)
- **Maximum Sequence Length:** 384 tokens
- **Output Dimensionality:** 768 dimensions
- **Similarity Function:** Cosine Similarity
### Model Sources
- **Documentation:** [Sentence Transformers Documentation](https://sbert.net)
- **Repository:** [Sentence Transformers on GitHub](https://github.com/UKPLab/sentence-transformers)
- **Hugging Face:** [Sentence Transformers on Hugging Face](https://huggingface.co/models?library=sentence-transformers)
### Full Model Architecture
```
SentenceTransformer(
(0): Transformer({'max_seq_length': 384, 'do_lower_case': False, 'architecture': 'MPNetModel'})
(1): Pooling({'word_embedding_dimension': 768, 'pooling_mode_cls_token': False, 'pooling_mode_mean_tokens': True, 'pooling_mode_max_tokens': False, 'pooling_mode_mean_sqrt_len_tokens': False, 'pooling_mode_weightedmean_tokens': False, 'pooling_mode_lasttoken': False, 'include_prompt': True})
(2): Normalize()
)
```
## Usage
### Direct Usage (Sentence Transformers)
First install the Sentence Transformers library:
```bash
pip install -U sentence-transformers
```
Then you can load this model and run inference.
```python
from sentence_transformers import SentenceTransformer
# Download from the 🤗 Hub
model = SentenceTransformer("FritzStack/mpnet_MH_embedding")
# Run inference
sentences = [
'Do you feel sad or unhappy?',
'Im not exactly depressed, at least not all of the time.',
'does anyone feel like they cant be sad',
]
embeddings = model.encode(sentences)
print(embeddings.shape)
# [3, 768]
# Get the similarity scores for the embeddings
similarities = model.similarity(embeddings, embeddings)
print(similarities)
# tensor([[ 1.0000, 0.7532, -0.4572],
# [ 0.7532, 1.0000, -0.0545],
# [-0.4572, -0.0545, 1.0000]])
```
## Training Details
### Training Dataset
#### Unnamed Dataset
* Size: 4,615 training samples
* Columns: anchor, positive, and negative
* Approximate statistics based on the first 1000 samples:
| | anchor | positive | negative |
|:--------|:----------------------------------------------------------------------------------|:----------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------|
| type | string | string | string |
| details | - min: 9 tokens
- mean: 13.63 tokens
- max: 17 tokens
| - min: 5 tokens
- mean: 20.7 tokens
- max: 169 tokens
| - min: 4 tokens
- mean: 42.11 tokens
- max: 384 tokens
|
* Samples:
| anchor | positive | negative |
|:-----------------------------------------|:------------------------------------------|:------------------------------------------------------------------------------------------------------------------------------------------------------------------|
| Do you feel sad or unhappy? | I do not feel sad. | I've been suffering my whole life, and it's currently at its peak :( |
| Do you feel sad or unhappy? | I feel sad much of the time. | Things will get better, just focus more in the positive rather than the negative |
| Do you feel sad or unhappy? | I am sad all the time. | That's why I understand I'm terrible, because it's wrong I get annoyed by that, people should do what they want, but I just can't stand being alone. |
* Loss: [TripletLoss](https://sbert.net/docs/package_reference/sentence_transformer/losses.html#tripletloss) with these parameters:
```json
{
"distance_metric": "TripletDistanceMetric.COSINE",
"triplet_margin": 0.5
}
```
### Training Hyperparameters
#### Non-Default Hyperparameters
- `per_device_train_batch_size`: 2
- `gradient_accumulation_steps`: 8
- `warmup_steps`: 100
- `fp16`: True
#### All Hyperparameters
Click to expand
- `overwrite_output_dir`: False
- `do_predict`: False
- `eval_strategy`: no
- `prediction_loss_only`: True
- `per_device_train_batch_size`: 2
- `per_device_eval_batch_size`: 8
- `per_gpu_train_batch_size`: None
- `per_gpu_eval_batch_size`: None
- `gradient_accumulation_steps`: 8
- `eval_accumulation_steps`: None
- `torch_empty_cache_steps`: None
- `learning_rate`: 5e-05
- `weight_decay`: 0.0
- `adam_beta1`: 0.9
- `adam_beta2`: 0.999
- `adam_epsilon`: 1e-08
- `max_grad_norm`: 1.0
- `num_train_epochs`: 3
- `max_steps`: -1
- `lr_scheduler_type`: linear
- `lr_scheduler_kwargs`: {}
- `warmup_ratio`: 0.0
- `warmup_steps`: 100
- `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
- `bf16`: False
- `fp16`: True
- `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`: 0
- `dataloader_prefetch_factor`: None
- `past_index`: -1
- `disable_tqdm`: False
- `remove_unused_columns`: True
- `label_names`: None
- `load_best_model_at_end`: False
- `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`: adamw_torch_fused
- `optim_args`: None
- `adafactor`: False
- `group_by_length`: False
- `length_column_name`: length
- `project`: huggingface
- `trackio_space_id`: trackio
- `ddp_find_unused_parameters`: None
- `ddp_bucket_cap_mb`: None
- `ddp_broadcast_buffers`: False
- `dataloader_pin_memory`: True
- `dataloader_persistent_workers`: False
- `skip_memory_metrics`: True
- `use_legacy_prediction_loop`: False
- `push_to_hub`: False
- `resume_from_checkpoint`: None
- `hub_model_id`: None
- `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`: no
- `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`: True
- `prompts`: None
- `batch_sampler`: batch_sampler
- `multi_dataset_batch_sampler`: proportional
- `router_mapping`: {}
- `learning_rate_mapping`: {}